WorldWideScience

Sample records for identify gene clusters

  1. Comparative Analysis of Cluster Validity Indices in Identifying Some Possible Genes Mediating Certain Cancers.

    Science.gov (United States)

    Ghosh, Anupam; Dhara, Bibhas Chandra; De, Rajat K

    2013-04-01

    In this article, we compare the performance of 19 cluster validity indices, in identifying some possible genes mediating certain cancers, based on gene expression data. For the purpose of this comparison, we have developed a method. The proposed method involves cluster generation, selection of the best k-value or c-values, cluster identification, identifying the altered gene cluster, scoring an altered gene cluster and determining the best k-value or c-value exploring through biological repositories. The effectiveness of the method has been demonstrated on three gene expression data sets dealing with human lung cancer, colon cancer, and leukemia. Here, we have used three clustering algorithms, i.e., k-means, PAM and fuzzy c-means. We have used biochemical pathways related to these cancers and p-value statistics for validating the study. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. CTDGFinder: A Novel Homology-Based Algorithm for Identifying Closely Spaced Clusters of Tandemly Duplicated Genes.

    Science.gov (United States)

    Ortiz, Juan F; Rokas, Antonis

    2017-01-01

    Closely spaced clusters of tandemly duplicated genes (CTDGs) contribute to the diversity of many phenotypes, including chemosensation, snake venom, and animal body plans. CTDGs have traditionally been identified subjectively as genomic neighborhoods containing several gene duplicates in close proximity; however, CTDGs are often highly variable with respect to gene number, intergenic distance, and synteny. This lack of formal definition hampers the study of CTDG evolutionary dynamics and the discovery of novel CTDGs in the exponentially growing body of genomic data. To address this gap, we developed a novel homology-based algorithm, CTDGFinder, which formalizes and automates the identification of CTDGs by examining the physical distribution of individual members of families of duplicated genes across chromosomes. Application of CTDGFinder accurately identified CTDGs for many well-known gene clusters (e.g., Hox and beta-globin gene clusters) in the human, mouse and 20 other mammalian genomes. Differences between previously annotated gene clusters and our inferred CTDGs were due to the exclusion of nonhomologs that have historically been considered parts of specific gene clusters, the inclusion or absence of genes between the CTDGs and their corresponding gene clusters, and the splitting of certain gene clusters into distinct CTDGs. Examination of human genes showing tissue-specific enhancement of their expression by CTDGFinder identified members of several well-known gene clusters (e.g., cytochrome P450s and olfactory receptors) and revealed that they were unequally distributed across tissues. By formalizing and automating CTDG identification, CTDGFinder will facilitate understanding of CTDG evolutionary dynamics, their functional implications, and how they are associated with phenotypic diversity. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e

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

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    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.

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

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    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.

  5. A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data

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    Tcha Hong

    2008-01-01

    Full Text Available Abstract Background The previous studies of genome-wide expression patterns show that a certain percentage of genes are cell cycle regulated. The expression data has been analyzed in a number of different ways to identify cell cycle dependent genes. In this study, we pose the hypothesis that cell cycle dependent genes are considered as oscillating systems with a rhythm, i.e. systems producing response signals with period and frequency. Therefore, we are motivated to apply the theory of multivariate phase synchronization for clustering cell cycle specific genome-wide expression data. Results We propose the strategy to find groups of genes according to the specific biological process by analyzing cell cycle specific gene expression data. To evaluate the propose method, we use the modified Kuramoto model, which is a phase governing equation that provides the long-term dynamics of globally coupled oscillators. With this equation, we simulate two groups of expression signals, and the simulated signals from each group shares their own common rhythm. Then, the simulated expression data are mixed with randomly generated expression data to be used as input data set to the algorithm. Using these simulated expression data, it is shown that the algorithm is able to identify expression signals that are involved in the same oscillating process. We also evaluate the method with yeast cell cycle expression data. It is shown that the output clusters by the proposed algorithm include genes, which are closely associated with each other by sharing significant Gene Ontology terms of biological process and/or having relatively many known biological interactions. Therefore, the evaluation analysis indicates that the method is able to identify expression signals according to the specific biological process. Our evaluation analysis also indicates that some portion of output by the proposed algorithm is not obtainable by the traditional clustering algorithm with

  6. Epigenetic characterization of the growth hormone gene identifies SmcHD1 as a regulator of autosomal gene clusters.

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    Shabnam Massah

    Full Text Available Regulatory elements for the mouse growth hormone (GH gene are located distally in a putative locus control region (LCR in addition to key elements in the promoter proximal region. The role of promoter DNA methylation for GH gene regulation is not well understood. Pit-1 is a POU transcription factor required for normal pituitary development and obligatory for GH gene expression. In mammals, Pit-1 mutations eliminate GH production resulting in a dwarf phenotype. In this study, dwarf mice illustrated that Pit-1 function was obligatory for GH promoter hypomethylation. By monitoring promoter methylation levels during developmental GH expression we found that the GH promoter became hypomethylated coincident with gene expression. We identified a promoter differentially methylated region (DMR that was used to characterize a methylation-dependent DNA binding activity. Upon DNA affinity purification using the DMR and nuclear extracts, we identified structural maintenance of chromosomes hinge domain containing -1 (SmcHD1. To better understand the role of SmcHD1 in genome-wide gene expression, we performed microarray analysis and compared changes in gene expression upon reduced levels of SmcHD1 in human cells. Knock-down of SmcHD1 in human embryonic kidney (HEK293 cells revealed a disproportionate number of up-regulated genes were located on the X-chromosome, but also suggested regulation of genes on non-sex chromosomes. Among those, we identified several genes located in the protocadherin β cluster. In addition, we found that imprinted genes in the H19/Igf2 cluster associated with Beckwith-Wiedemann and Silver-Russell syndromes (BWS & SRS were dysregulated. For the first time using human cells, we showed that SmcHD1 is an important regulator of imprinted and clustered genes.

  7. Non-ribosomal peptide synthetases: Identifying the cryptic gene clusters and decoding the natural product

    Indian Academy of Sciences (India)

    MANGAL SINGH; SANDEEP CHAUDHARY; DIPTI SAREEN

    2017-03-01

    Non-ribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) present in bacteria and fungi are themajor multi-modular enzyme complexes which synthesize secondary metabolites like the pharmacologically importantantibiotics and siderophores. Each of the multiple modules of an NRPS activates a different amino or aryl acid,followed by their condensation to synthesize a linear or cyclic natural product. The studies on NRPS domains, theknowledge of their gene cluster architecture and tailoring enzymes have helped in the in silico genetic screening of theever-expanding sequenced microbial genomic data for the identification of novel NRPS/PKS clusters and thusdeciphering novel non-ribosomal peptides (NRPs). Adenylation domain is an integral part of the NRPSs and is thesubstrate selecting unit for the final assembled NRP. In some cases, it also requires a small protein, the MbtHhomolog, for its optimum activity. The presence of putative adenylation domain and MbtH homologs in a sequencedgenome can help identify the novel secondary metabolite producers. The role of the adenylation domain in the NRPSgene clusters and its characterization as a tool for the discovery of novel cryptic NRPS gene clusters are discussed.

  8. Onto-CC: a web server for identifying Gene Ontology conceptual clusters

    Science.gov (United States)

    Romero-Zaliz, R.; del Val, C.; Cobb, J. P.; Zwir, I.

    2008-01-01

    The Gene Ontology (GO) vocabulary has been extensively explored to analyze the functions of coexpressed genes. However, despite its extended use in Biology and Medical Sciences, there are still high levels of uncertainty about which ontology (i.e. Molecular Process, Cellular Component or Molecular Function) should be used, and at which level of specificity. Moreover, the GO database can contain incomplete information resulting from human annotations, or highly influenced by the available knowledge about a specific branch in an ontology. In spite of these drawbacks, there is a trend to ignore these problems and even use GO terms to conduct searches of gene expression profiles (i.e. expression + GO) instead of more cautious approaches that just consider them as an independent source of validation (i.e. expression versus GO). Consequently, propagating the uncertainty and producing biased analysis of the required gene grouping hypotheses. We proposed a web tool, Onto-CC, as an automatic method specially suited for independent explanation/validation of gene grouping hypotheses (e.g. coexpressed genes) based on GO clusters (i.e. expression versus GO). Onto-CC approach reduces the uncertainty of the queries by identifying optimal conceptual clusters that combine terms from different ontologies simultaneously, as well as terms defined at different levels of specificity in the GO hierarchy. To do so, we implemented the EMO-CC methodology to find clusters in structural databases [GO Directed acyclic Graph (DAG) tree], inspired on Conceptual Clustering algorithms. This approach allows the management of optimal cluster sets as potential parallel hypotheses, guided by multiobjective/multimodal optimization techniques. Therefore, we can generate alternative and, still, optimal explanations of queries that can provide new insights for a given problem. Onto-CC has been successfully used to test different medical and biological hypotheses including the explanation and prediction of

  9. An ensemble method for identifying regulatory circuits with special reference to the qa gene cluster of Neurospora crassa

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    Battogtokh, D.; Asch, D. K.; Case, M. E.; Arnold, J.; Schüttler, H.-B.

    2002-01-01

    A chemical reaction network for the regulation of the quinic acid (qa) gene cluster of Neurospora crassa is proposed. An efficient Monte Carlo method for walking through the parameter space of possible chemical reaction networks is developed to identify an ensemble of deterministic kinetics models with rate constants consistent with RNA and protein profiling data. This method was successful in identifying a model ensemble fitting available RNA profiling data on the qa gene cluster. PMID:12477937

  10. New Alzheimer amyloid beta responsive genes identified in human neuroblastoma cells by hierarchical clustering.

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    Markus Uhrig

    Full Text Available Alzheimer's disease (AD is characterized by neuronal degeneration and cell loss. Abeta(42, in contrast to Abeta(40, is thought to be the pathogenic form triggering the pathological cascade in AD. In order to unravel overall gene regulation we monitored the transcriptomic responses to increased or decreased Abeta(40 and Abeta(42 levels, generated and derived from its precursor C99 (C-terminal fragment of APP comprising 99 amino acids in human neuroblastoma cells. We identified fourteen differentially expressed transcripts by hierarchical clustering and discussed their involvement in AD. These fourteen transcripts were grouped into two main clusters each showing distinct differential expression patterns depending on Abeta(40 and Abeta(42 levels. Among these transcripts we discovered an unexpected inverse and strong differential expression of neurogenin 2 (NEUROG2 and KIAA0125 in all examined cell clones. C99-overexpression had a similar effect on NEUROG2 and KIAA0125 expression as a decreased Abeta(42/Abeta(40 ratio. Importantly however, an increased Abeta(42/Abeta(40 ratio, which is typical of AD, had an inverse expression pattern of NEUROG2 and KIAA0125: An increased Abeta(42/Abeta(40 ratio up-regulated NEUROG2, but down-regulated KIAA0125, whereas the opposite regulation pattern was observed for a decreased Abeta(42/Abeta(40 ratio. We discuss the possibilities that the so far uncharacterized KIAA0125 might be a counter player of NEUROG2 and that KIAA0125 could be involved in neurogenesis, due to the involvement of NEUROG2 in developmental neural processes.

  11. Gene Cluster Statistics with Gene Families

    Science.gov (United States)

    Durand, Dannie

    2009-01-01

    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. Comparative analysis of a cryptic thienamycin-like gene cluster identified in Streptomyces flavogriseus by genome mining.

    Science.gov (United States)

    Blanco, Gloria

    2012-06-01

    In silico database searches allowed the identification in the S. flavogriseus ATCC 33331 genome of a carbapenem gene cluster highly related to the S. cattleya thienamycin one. This is the second cluster found for a complex highly substituted carbapenem. Comparative analysis revealed that both gene clusters display a high degree of synteny in gene organization and in protein conservation. Although the cluster appears to be silent under our laboratory conditions, the putative metabolic product was predicted from bioinformatics analyses using sequence comparison tools. These data, together with previous reports concerning epithienamycins production by S. flavogriseus strains, suggest that the cluster metabolic product might be a thienamycin-like carbapenem, possibly the epimeric epithienamycin. This finding might help in understanding the biosynthetic pathway to thienamycin and other highly substituted carbapenems. It also provides another example of genome mining in Streptomyces sequenced genomes as a powerful approach for novel antibiotic discovery.

  13. Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives

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    Hummel Oliver

    2009-02-01

    Full Text Available Abstract Background Mouse embryonic stem (ES cells remain pluripotent in vitro when grown in the presence of the cytokine Leukaemia Inhibitory Factor (LIF. Identification of LIF targets and of genes regulating the transition between pluripotent and early differentiated cells is a critical step for understanding the control of ES cell pluripotency. Results By gene profiling studies carried out with mRNAs from ES cells and their early derivatives treated or not with LIF, we have identified i LIF-dependent genes, highly expressed in pluripotent cells, whose expression level decreases sharply upon LIF withdrawal [Pluri genes], ii LIF induced genes [Lifind genes] whose expression is differentially regulated depending upon cell context and iii genes specific to the reversible or irreversible committed states. In addition, by hierarchical gene clustering, we have identified, among eight independent gene clusters, two atypical groups of genes, whose expression level was highly modulated in committed cells only. Computer based analyses led to the characterization of different sub-types of Pluri and Lifind genes, and revealed their differential modulation by Oct4 or Nanog master genes. Individual knock down of a selection of Pluri and Lifind genes leads to weak changes in the expression of early differentiation markers, in cell growth conditions in which these master genes are still expressed. Conclusion We have identified different sets of LIF-regulated genes depending upon the cell state (reversible or irreversible commitment, which allowed us to present a novel global view of LIF responses. We are also reporting on the identification of genes whose expression is strictly regulated during the commitment step. Furthermore, our studies identify sub-networks of genes with a restricted expression in pluripotent ES cells, whose down regulation occurs while the master knot (composed of OCT4, SOX2 and NANOG is still expressed and which might be down

  14. A genome-wide association study of the maize hypersensitive defense response identifies genes that cluster in related pathways.

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    Bode A Olukolu

    2014-08-01

    Full Text Available Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR, a rapid localized cell death that limits pathogen spread and is mediated by resistance (R- genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21, were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs. Genome-wide association (GWA analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.

  15. Identifying Geographic Clusters: A Network Analytic Approach

    CERN Document Server

    Catini, Roberto; Penner, Orion; Riccaboni, Massimo

    2015-01-01

    In recent years there has been a growing interest in the role of networks and clusters in the global economy. Despite being a popular research topic in economics, sociology and urban studies, geographical clustering of human activity has often studied been by means of predetermined geographical units such as administrative divisions and metropolitan areas. This approach is intrinsically time invariant and it does not allow one to differentiate between different activities. Our goal in this paper is to present a new methodology for identifying clusters, that can be applied to different empirical settings. We use a graph approach based on k-shell decomposition to analyze world biomedical research clusters based on PubMed scientific publications. We identify research institutions and locate their activities in geographical clusters. Leading areas of scientific production and their top performing research institutions are consistently identified at different geographic scales.

  16. In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

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    Kristopher J. L. Irizarry

    2016-01-01

    Full Text Available Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1 that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons.

  17. In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

    Science.gov (United States)

    2016-01-01

    Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

  18. Identifying trait clusters by linkage profiles: application in genetical genomics.

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    Sampson, Joshua N; Self, Steven G

    2008-04-01

    Genes often regulate multiple traits. Identifying clusters of traits influenced by a common group of genes helps elucidate regulatory networks and can improve linkage mapping. We show that the Pearson correlation coefficient, rho L, between two LOD score profiles can, with high specificity and sensitivity, identify pairs of genes that have their transcription regulated by shared quantitative trait loci (QTL). Furthermore, using theoretical and/or empirical methods, we can approximate the distribution of rho L under the null hypothesis of no common QTL. Therefore, it is possible to calculate P-values and false discovery rates for testing whether two traits share common QTL. We then examine the properties of rho L through simulation and use rho L to cluster genes in a genetical genomics experiment examining Saccharomyces cerevisiae. Simulations show that rho L can have more power than the clustering methods currently used in genetical genomics. Combining experimental results with Gene Ontology (GO) annotations show that genes within a purported cluster often share similar function. R-code included in online Supplementary Material.

  19. FunGeneClusterS

    DEFF Research Database (Denmark)

    Vesth, Tammi Camilla; Brandl, Julian; Andersen, Mikael Rørdam

    2016-01-01

    and industrial biotechnology applications. We have previously published a method for accurate prediction of clusters from genome and transcriptome data, which could also suggest cross-chemistry, however, this method was limited both in the number of parameters which could be adjusted as well as in user......Secondary metabolites of fungi are receiving an increasing amount of interest due to their prolific bioactivities and the fact that fungal biosynthesis of secondary metabolites often occurs from co-regulated and co-located gene clusters. This makes the gene clusters attractive for synthetic biology...

  20. A genome-wide screen identifies a single β-defensin gene cluster in the chicken: implications for the origin and evolution of mammalian defensins

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    Xiao Yanjing

    2004-08-01

    Full Text Available Abstract Background Defensins comprise a large family of cationic antimicrobial peptides that are characterized by the presence of a conserved cysteine-rich defensin motif. Based on the spacing pattern of cysteines, these defensins are broadly divided into five groups, namely plant, invertebrate, α-, β-, and θ-defensins, with the last three groups being mostly found in mammalian species. However, the evolutionary relationships among these five groups of defensins remain controversial. Results Following a comprehensive screen, here we report that the chicken genome encodes a total of 13 different β-defensins but with no other groups of defensins being discovered. These chicken β-defensin genes, designated as Gallinacin 1–13, are clustered densely within a 86-Kb distance on the chromosome 3q3.5-q3.7. The deduced peptides vary from 63 to 104 amino acid residues in length sharing the characteristic defensin motif. Based on the tissue expression pattern, 13 β-defensin genes can be divided into two subgroups with Gallinacin 1–7 being predominantly expressed in bone marrow and the respiratory tract and the remaining genes being restricted to liver and the urogenital tract. Comparative analysis of the defensin clusters among chicken, mouse, and human suggested that vertebrate defensins have evolved from a single β-defensin-like gene, which has undergone rapid duplication, diversification, and translocation in various vertebrate lineages during evolution. Conclusions We conclude that the chicken genome encodes only β-defensin sequences and that all mammalian defensins are evolved from a common β-defensin-like ancestor. The α-defensins arose from β-defensins by gene duplication, which may have occurred after the divergence of mammals from other vertebrates, and θ-defensins have arisen from α-defensins specific to the primate lineage. Further analysis of these defensins in different vertebrate lineages will shed light on the mechanisms of

  1. Pyrosequencing-based analysis reveals a novel capsular gene cluster in a KPC-producing Klebsiella pneumoniae clinical isolate identified in Brazil

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    Ramos Pablo Ivan

    2012-08-01

    Full Text Available Abstract Background An important virulence factor of Klebsiella pneumoniae is the production of capsular polysaccharide (CPS, a thick mucus layer that allows for evasion of the host's defense and creates a barrier against antibacterial peptides. CPS production is driven mostly by the expression of genes located in a locus called cps, and the resulting structure is used to distinguish between different serotypes (K types. In this study, we report the unique genetic organization of the cps cluster from K. pneumoniae Kp13, a clinical isolate recovered during a large outbreak of nosocomial infections that occurred in a Brazilian teaching hospital. Results A pyrosequencing-based approach showed that the cps region of Kp13 (cpsKp13 is 26.4 kbp in length and contains genes common, although not universal, to other strains, such as the rmlBADC operon that codes for L-rhamnose synthesis. cpsKp13 also presents some unique features, like the inversion of the wzy gene and a unique repertoire of glycosyltransferases. In silico comparison of cpsKp13 RFLP pattern with 102 previously published cps PCR-RFLP patterns showed that cpsKp13 is distinct from the C patterns of all other K serotypes. Furthermore, in vitro serotyping showed only a weak reaction with capsular types K9 and K34. We confirm that K9 cps shares common genes with cpsKp13 such as the rmlBADC operon, but lacks features like uge and Kp13-specific glycosyltransferases, while K34 capsules contain three of the five sugars that potentially form the Kp13 CPS. Conclusions We report the first description of a cps cluster from a Brazilian clinical isolate of a KPC-producing K. pneumoniae. The gathered data including K-serotyping support that Kp13’s K-antigen belongs to a novel capsular serotype. The CPS of Kp13 probably includes L-rhamnose and D-galacturonate in its structure, among other residues. Because genes involved in L-rhamnose biosynthesis are absent in humans, this pathway may represent

  2. Computing gene expression data with a knowledge-based gene clustering approach.

    Science.gov (United States)

    Rosa, Bruce A; Oh, Sookyung; Montgomery, Beronda L; Chen, Jin; Qin, Wensheng

    2010-01-01

    Computational analysis methods for gene expression data gathered in microarray experiments can be used to identify the functions of previously unstudied genes. While obtaining the expression data is not a difficult task, interpreting and extracting the information from the datasets is challenging. In this study, a knowledge-based approach which identifies and saves important functional genes before filtering based on variability and fold change differences was utilized to study light regulation. Two clustering methods were used to cluster the filtered datasets, and clusters containing a key light regulatory gene were located. The common genes to both of these clusters were identified, and the genes in the common cluster were ranked based on their coexpression to the key gene. This process was repeated for 11 key genes in 3 treatment combinations. The initial filtering method reduced the dataset size from 22,814 probes to an average of 1134 genes, and the resulting common cluster lists contained an average of only 14 genes. These common cluster lists scored higher gene enrichment scores than two individual clustering methods. In addition, the filtering method increased the proportion of light responsive genes in the dataset from 1.8% to 15.2%, and the cluster lists increased this proportion to 18.4%. The relatively short length of these common cluster lists compared to gene groups generated through typical clustering methods or coexpression networks narrows the search for novel functional genes while increasing the likelihood that they are biologically relevant.

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

    OpenAIRE

    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 numb...

  4. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

    Ray, Shubhra Sankar; Bandyopadhyay, Sanghamitra; Pal, Sankar K

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions.Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  5. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  6. Identify Implicit Communities by Graph Clustering

    Institute of Scientific and Technical Information of China (English)

    YANG Nan; MENG Xiaofeng

    2006-01-01

    How to find these communities is an important research work. Recently, community discovery are mainly categorized to HITS algorithm, bipartite cores algorithm and maximum flow/minimum cut framework. In this paper, we proposed a new method to extract communities. The MCL algorithm, which is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm is used to extract communities. By putting mirror deleting procedure behind graph clustering, we decrease comparing cost considerably. After MCL and mirror deletion, we use community member select algorithm to produce the sets of community candidates. The experiment and results show the new method works effectively and properly.

  7. Deletion of a gene cluster for [Ni-Fe] hydrogenase maturation in the anaerobic hyperthermophilic bacterium Caldicellulosiruptor bescii identifies its role in hydrogen metabolism.

    Science.gov (United States)

    Cha, Minseok; Chung, Daehwan; Westpheling, Janet

    2016-02-01

    The anaerobic, hyperthermophlic, cellulolytic bacterium Caldicellulosiruptor bescii grows optimally at ∼80 °C and effectively degrades plant biomass without conventional pretreatment. It utilizes a variety of carbohydrate carbon sources, including both C5 and C6 sugars, released from plant biomass and produces lactate, acetate, CO2, and H2 as primary fermentation products. The C. bescii genome encodes two hydrogenases, a bifurcating [Fe-Fe] hydrogenase and a [Ni-Fe] hydrogenase. The [Ni-Fe] hydrogenase is the most widely distributed in nature and is predicted to catalyze hydrogen production and to pump protons across the cellular membrane creating proton motive force. Hydrogenases are the key enzymes in hydrogen metabolism and their crystal structure reveals complexity in the organization of their prosthetic groups suggesting extensive maturation of the primary protein. Here, we report the deletion of a cluster of genes, hypABFCDE, required for maturation of the [Ni-Fe] hydrogenase. These proteins are specific for the hydrogenases they modify and are required for hydrogenase activity. The deletion strain grew more slowly than the wild type or the parent strain and produced slightly less hydrogen overall, but more hydrogen per mole of cellobiose. Acetate yield per mole of cellobiose was increased ∼67 % and ethanol yield per mole of cellobiose was decreased ∼39 %. These data suggest that the primary role of the [Ni-Fe] hydrogenase is to generate a proton gradient in the membrane driving ATP synthesis and is not the primary enzyme for hydrogen catalysis. In its absence, ATP is generated from increased acetate production resulting in more hydrogen produced per mole of cellobiose.

  8. 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

  9. 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

  10. Identifying Peer Institutions Using Cluster Analysis

    Science.gov (United States)

    Boronico, Jess; Choksi, Shail S.

    2012-01-01

    The New York Institute of Technology's (NYIT) School of Management (SOM) wishes to develop a list of peer institutions for the purpose of benchmarking and monitoring/improving performance against other business schools. The procedure utilizes relevant criteria for the purpose of establishing this peer group by way of a cluster analysis. The…

  11. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

    Science.gov (United States)

    Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

    2015-09-01

    We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Super-paramagnetic clustering of yeast gene expression profiles

    CERN Document Server

    Getz, G; Domany, E; Zhang, M Q

    2000-01-01

    High-density DNA arrays, used to monitor gene expression at a genomic scale, have produced vast amounts of information which require the development of efficient computational methods to analyze them. The important first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of a novel clustering algorithm, Super-Paramagnetic Clustering (SPC) to analysis of gene expression profiles that were generated recently during a study of the yeast cell cycle. SPC was used to organize genes into biologically relevant clusters that are suggestive for their co-regulation. Some of the advantages of SPC are its robustness against noise and initialization, a clear signature of cluster formation and splitting, and an unsupervised self-organized determination of the number of clusters at each resolution. Our analysis revealed interesting correlated behavior of several groups of genes which has not been previously identified.

  13. Super-paramagnetic clustering of yeast gene expression profiles

    Science.gov (United States)

    Getz, G.; Levine, E.; Domany, E.; Zhang, M. Q.

    2000-04-01

    High-density DNA arrays, used to monitor gene expression at a genomic scale, have produced vast amounts of information which require the development of efficient computational methods to analyze them. The important first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of a novel clustering algorithm, super-paramagnetic clustering (SPC) to analysis of gene expression profiles that were generated recently during a study of the yeast cell cycle. SPC was used to organize genes into biologically relevant clusters that are suggestive for their co-regulation. Some of the advantages of SPC are its robustness against noise and initialization, a clear signature of cluster formation and splitting, and an unsupervised self-organized determination of the number of clusters at each resolution. Our analysis revealed interesting correlated behavior of several groups of genes which has not been previously identified.

  14. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

    Science.gov (United States)

    Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

    2015-01-01

    Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

  15. NIH Researchers Identify OCD Risk Gene

    Science.gov (United States)

    ... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

  16. Genomic Analyses of Bacterial Porin-Cytochrome Gene Clusters

    Directory of Open Access Journals (Sweden)

    Liang eShi

    2014-11-01

    Full Text Available The porin-cytochrome (Pcc protein complex is responsible for trans-outer membrane electron transfer during extracellular reduction of Fe(III by the dissimilatory metal-reducing bacterium Geobacter sulfurreducens PCA. The identified and characterized Pcc complex of G. sulfurreducens PCA consists of a porin-like outer-membrane protein, a periplasmic 8-heme c-type cytochrome (c-Cyt and an outer-membrane 12-heme c-Cyt, and the genes encoding the Pcc proteins are clustered in the same regions of genome (i.e., the pcc gene clusters of G. sulfurreducens PCA. A survey of additionally microbial genomes has identified the pcc gene clusters in all sequenced Geobacter spp. and other bacteria from six different phyla, including Anaeromyxobacter dehalogenans 2CP-1, A. dehalogenans 2CP-C, Anaeromyxobacter sp. K, Candidatus Kuenenia stuttgartiensis, Denitrovibrio acetiphilus DSM 12809, Desulfurispirillum indicum S5, Desulfurivibrio alkaliphilus AHT2, Desulfurobacterium thermolithotrophum DSM 11699, Desulfuromonas acetoxidans DSM 684, Ignavibacterium album JCM 16511, and Thermovibrio ammonificans HB-1. The numbers of genes in the pcc gene clusters vary, ranging from two to nine. Similar to the metal-reducing (Mtr gene clusters of other Fe(III-reducing bacteria, such as Shewanella spp., additional genes that encode putative c-Cyts with predicted cellular localizations at the cytoplasmic membrane, periplasm and outer membrane often associate with the pcc gene clusters. This suggests that the Pcc-associated c-Cyts may be part of the pathways for extracellular electron transfer reactions. The presence of pcc gene clusters in the microorganisms that do not reduce solid-phase Fe(III and Mn(IV oxides, such as D. alkaliphilus AHT2 and I. album JCM 16511, also suggests that some of the pcc gene clusters may be involved in extracellular electron transfer reactions with the substrates other than Fe(III and Mn(IV oxides.

  17. Clustering of gene ontology terms in genomes.

    Science.gov (United States)

    Tiirikka, Timo; Siermala, Markku; Vihinen, Mauno

    2014-10-25

    Although protein coding genes occupy only a small fraction of genomes in higher species, they are not randomly distributed within or between chromosomes. Clustering of genes with related function(s) and/or characteristics has been evident at several different levels. To study how common the clustering of functionally related genes is and what kind of functions the end products of these genes are involved, we collected gene ontology (GO) terms for complete genomes and developed a method to detect previously undefined gene clustering. Exhaustive analysis was performed for seven widely studied species ranging from human to Escherichia coli. To overcome problems related to varying gene lengths and densities, a novel method was developed and a fixed number of genes were analyzed irrespective of the genome span covered. Statistically very significant GO term clustering was apparent in all the investigated genomes. The analysis window, which ranged from 5 to 50 consecutive genes, revealed extensive GO term clusters for genes with widely varying functions. Here, the most interesting and significant results are discussed and the complete dataset for each analyzed species is available at the GOme database at http://bioinf.uta.fi/GOme. The results indicated that clusters of genes with related functions are very common, not only in bacteria, in which operons are frequent, but also in all the studied species irrespective of how complex they are. There are some differences between species but in all of them GO term clusters are common and of widely differing sizes. The presented method can be applied to analyze any genome or part of a genome for which descriptive features are available, and thus is not restricted to ontology terms. This method can also be applied to investigate gene and protein expression patterns. The results pave a way for further studies of mechanisms that shape genome structure and evolutionary forces related to them. Copyright © 2014 Elsevier B.V. All

  18. Novel LanT associated lantibiotic clusters identified by genome database mining.

    Directory of Open Access Journals (Sweden)

    Mangal Singh

    Full Text Available BACKGROUND: Frequent use of antibiotics has led to the emergence of antibiotic resistance in bacteria. Lantibiotic compounds are ribosomally synthesized antimicrobial peptides against which bacteria are not able to produce resistance, hence making them a good alternative to antibiotics. Nisin is the oldest and the most widely used lantibiotic, in food preservation, without having developed any significant resistance against it. Having their antimicrobial potential and a limited number, there is a need to identify novel lantibiotics. METHODOLOGY/FINDINGS: Identification of novel lantibiotic biosynthetic clusters from an ever increasing database of bacterial genomes, can provide a major lead in this direction. In order to achieve this, a strategy was adopted to identify novel lantibiotic biosynthetic clusters by screening the sequenced genomes for LanT homolog, which is a conserved lantibiotic transporter specific to type IB clusters. This strategy resulted in identification of 54 bacterial strains containing the LanT homologs, which are not the known lantibiotic producers. Of these, 24 strains were subjected to a detailed bioinformatic analysis to identify genes encoding for precursor peptides, modification enzyme, immunity and quorum sensing proteins. Eight clusters having two LanM determinants, similar to haloduracin and lichenicidin were identified, along with 13 clusters having a single LanM determinant as in mersacidin biosynthetic cluster. Besides these, orphan LanT homologs were also identified which might be associated with novel bacteriocins, encoded somewhere else in the genome. Three identified gene clusters had a C39 domain containing LanT transporter, associated with the LanBC proteins and double glycine type precursor peptides, the only known example of such a cluster is that of salivaricin. CONCLUSION: This study led to the identification of 8 novel putative two-component lantibiotic clusters along with 13 having a single LanM and

  19. Coupled Two-Way Clustering Analysis of Breast Cancer and Colon Cancer Gene Expression Data

    CERN Document Server

    Getz, G; Kela, I; Domany, E; Notterman, D A; Getz, Gad; Gal, Hilah; Kela, Itai; Domany, Eytan; Notterman, Dan A.

    2003-01-01

    We present and review Coupled Two Way Clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.

  20. Minimum Information about a Biosynthetic Gene cluster

    NARCIS (Netherlands)

    Medema, M.H.; Kottmann, Renzo; Yilmaz, Pelin; Cummings, Matthew; Biggins, J.B.; Blin, Kai; Bruijn, De Irene; Chooi, Yit Heng; Claesen, Jan; Coates, R.C.; Cruz-Morales, Pablo; Duddela, Srikanth; Düsterhus, 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; Kötter, Peter; Krug, Daniel; Masschelein, Joleen; Melnik, Alexey V.; Mantovani, Simone M.; Monroe, Emily A.; Moore, Marcus; Moss, Nathan; Nützmann, Hans Wilhelm; Pan, Guohui; Pati, Amrita; Petras, Daniel; Reen, F.J.; 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-Gómez, Francisco; Bechthold, Andreas; Bode, Helge B.; Borriss, Rainer; Brady, Sean F.; Brakhage, Axel A.; Caffrey, Patrick; Cheng, Yi Qiang; Clardy, Jon; Cox, Russell J.; Mot, De René; Donadio, Stefano; Donia, Mohamed S.; Donk, Van Der 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; Höfte, 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; Méndez, Carmen; Metsä-Ketelä, Mikko; Micklefield, Jason; Mitchell, Douglas A.; Moore, Bradley S.; Moreira, Leonilde M.; Müller, 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, Jörn; Ploux, Olivier; Raaijmakers, Jos M.; Salas, José A.; Schmitt, Esther K.; Scott, Barry; Seipke, Ryan F.; Shen, Ben; Sherman, David H.; Sivonen, Kaarina; Smanski, Michael J.; Sosio, Margherita; Stegmann, Evi; Süssmuth, Roderich D.; Tahlan, Kapil; Thomas, Christopher M.; Tang, Yi; Truman, Andrew W.; Viaud, Muriel; Walton, Jonathan D.; Walsh, Christopher T.; Weber, Tilmann; Wezel, Van Gilles P.; Wilkinson, Barrie; Willey, Joanne M.; Wohlleben, Wolfgang; Wright, Gerard D.; Ziemert, Nadine; Zhang, Changsheng; Zotchev, Sergey B.; Breitling, Rainer; Takano, Eriko; Glöckner, Frank Oliver

    2015-01-01

    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 exploi

  1. Clustering Algorithms: Their Application to Gene Expression Data

    Science.gov (United States)

    Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

    2016-01-01

    Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

  2. Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

    Science.gov (United States)

    van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

    2017-01-01

    In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.

  3. A Rough Set based Gene Expression Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    J. J. Emilyn

    2011-01-01

    Full Text Available Problem statement: Microarray technology helps in monitoring the expression levels of thousands of genes across collections of related samples. Approach: The main goal in the analysis of large and heterogeneous gene expression datasets was to identify groups of genes that get expressed in a set of experimental conditions. Results: Several clustering techniques have been proposed for identifying gene signatures and to understand their role and many of them have been applied to gene expression data, but with partial success. The main aim of this work was to develop a clustering algorithm that would successfully indentify gene patterns. The proposed novel clustering technique (RCGED provides an efficient way of finding the hidden and unique gene expression patterns. It overcomes the restriction of one object being placed in only one cluster. Conclusion/Recommendations: The proposed algorithm is termed intelligent because it automatically determines the optimum number of clusters. The proposed algorithm was experimented with colon cancer dataset and the results were compared with Rough Fuzzy K Means algorithm.

  4. Evolution of homeobox gene clusters in animals: the Giga-cluster and primary versus secondary clustering.

    Directory of Open Access Journals (Sweden)

    David Ellard Keith Ferrier

    2016-04-01

    Full Text Available The Hox gene cluster has been a major focus in evolutionary developmental biology. This is because of its key role in patterning animal development and widespread examples of changes in Hox genes being linked to the evolution of animal body plans and morphologies. Also, the distinctive organisation of the Hox genes into genomic clusters in which the order of the genes along the chromosome corresponds to the order of their activity along the embryo, or during a developmental process, has been a further source of great interest. This is known as Colinearity, and it provides a clear link between genome organisation and the regulation of genes during development, with distinctive changes marking evolutionary transitions. The Hox genes are not alone, however. The homeobox genes are a large super-class, of which the Hox genes are only a small subset, and an ever-increasing number of further gene clusters besides the Hox are being discovered. This is of great interest because of the potential for such gene clusters to help understand major evolutionary transitions, both in terms of changes to development and morphology as well as evolution of genome organisation. However, there is uncertainty in our understanding of homeobox gene cluster evolution at present. This relates to our still rudimentary understanding of the dynamics of genome rearrangements and evolution over the evolutionary timescales being considered when we compare lineages from across the animal kingdom. A major goal is to deduce whether particular instances of clustering are primary (conserved from ancient ancestral clusters or secondary (reassortment of genes into clusters in lineage-specific fashion. The following summary of the various instances of homeobox gene clusters in animals, and the hypotheses about their evolution, provides a framework for the future resolution of this uncertainty.

  5. Evolution of orthologous tandemly arrayed gene clusters

    Directory of Open Access Journals (Sweden)

    Bertrand Denis

    2011-10-01

    Full Text Available Abstract Background Tandemly Arrayed Gene (TAG clusters are groups of paralogous genes that are found adjacent on a chromosome. TAGs represent an important repertoire of genes in eukaryotes. In addition to tandem duplication events, TAG clusters are affected during their evolution by other mechanisms, such as inversion and deletion events, that affect the order and orientation of genes. The DILTAG algorithm developed in 1 makes it possible to infer a set of optimal evolutionary histories explaining the evolution of a single TAG cluster, from an ancestral single gene, through tandem duplications (simple or multiple, direct or inverted, deletions and inversion events. Results We present a general methodology, which is an extension of DILTAG, for the study of the evolutionary history of a set of orthologous TAG clusters in multiple species. In addition to the speciation events reflected by the phylogenetic tree of the considered species, the evolutionary events that are taken into account are simple or multiple tandem duplications, direct or inverted, simple or multiple deletions, and inversions. We analysed the performance of our algorithm on simulated data sets and we applied it to the protocadherin gene clusters of human, chimpanzee, mouse and rat. Conclusions Our results obtained on simulated data sets showed a good performance in inferring the total number and size distribution of duplication events. A limitation of the algorithm is however in dealing with multiple gene deletions, as the algorithm is highly exponential in this case, and becomes quickly intractable.

  6. Chicken rRNA Gene Cluster Structure.

    Directory of Open Access Journals (Sweden)

    Alexander G Dyomin

    Full Text Available Ribosomal RNA (rRNA genes, whose activity results in nucleolus formation, constitute an extremely important part of genome. Despite the extensive exploration into avian genomes, no complete description of avian rRNA gene primary structure has been offered so far. We publish a complete chicken rRNA gene cluster sequence here, including 5'ETS (1836 bp, 18S rRNA gene (1823 bp, ITS1 (2530 bp, 5.8S rRNA gene (157 bp, ITS2 (733 bp, 28S rRNA gene (4441 bp and 3'ETS (343 bp. The rRNA gene cluster sequence of 11863 bp was assembled from raw reads and deposited to GenBank under KT445934 accession number. The assembly was validated through in situ fluorescent hybridization analysis on chicken metaphase chromosomes using computed and synthesized specific probes, as well as through the reference assembly against de novo assembled rRNA gene cluster sequence using sequenced fragments of BAC-clone containing chicken NOR (nucleolus organizer region. The results have confirmed the chicken rRNA gene cluster validity.

  7. 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.

  8. 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.

  9. 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...

  10. A 6-gene signature identifies four molecular subgroups of neuroblastoma

    LENUS (Irish Health Repository)

    Abel, Frida

    2011-04-14

    Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and\\/or dead of disease, p < 0.05, Fisher\\'s exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group\\'s specific characteristics.

  11. Identifying clinical course patterns in SMS data using cluster analysis

    DEFF Research Database (Denmark)

    Kent, Peter; Kongsted, Alice

    2012-01-01

    ABSTRACT: BACKGROUND: Recently, there has been interest in using the short message service (SMS or text messaging), to gather frequent information on the clinical course of individual patients. One possible role for identifying clinical course patterns is to assist in exploring clinically importa...... of cluster analysis. More research is needed, especially head-to-head studies, to identify which technique is best to use under what circumstances.......ABSTRACT: BACKGROUND: Recently, there has been interest in using the short message service (SMS or text messaging), to gather frequent information on the clinical course of individual patients. One possible role for identifying clinical course patterns is to assist in exploring clinically important...... by spline analysis. However, cluster analysis of SMS data in its original untransformed form may be simpler and offer other advantages. Therefore, the aim of this study was to determine whether cluster analysis could be used for identifying clinical course patterns distinct from the pattern of the whole...

  12. Cluster analysis of clinical data identifies fibromyalgia subgroups.

    Directory of Open Access Journals (Sweden)

    Elisa Docampo

    Full Text Available INTRODUCTION: Fibromyalgia (FM is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. MATERIAL AND METHODS: 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. RESULTS: VARIABLES CLUSTERED INTO THREE INDEPENDENT DIMENSIONS: "symptomatology", "comorbidities" and "clinical scales". Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1, high symptomatology and comorbidities (Cluster 2, and high symptomatology but low comorbidities (Cluster 3, showing differences in measures of disease severity. CONCLUSIONS: We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.

  13. Filtering Genes for Cluster and Network Analysis

    Directory of Open Access Journals (Sweden)

    Parkhomenko Elena

    2009-06-01

    Full Text Available Abstract Background Prior to cluster analysis or genetic network analysis it is customary to filter, or remove genes considered to be irrelevant from the set of genes to be analyzed. Often genes whose variation across samples is less than an arbitrary threshold value are deleted. This can improve interpretability and reduce bias. Results This paper introduces modular models for representing network structure in order to study the relative effects of different filtering methods. We show that cluster analysis and principal components are strongly affected by filtering. Filtering methods intended specifically for cluster and network analysis are introduced and compared by simulating modular networks with known statistical properties. To study more realistic situations, we analyze simulated "real" data based on well-characterized E. coli and S. cerevisiae regulatory networks. Conclusion The methods introduced apply very generally, to any similarity matrix describing gene expression. One of the proposed methods, SUMCOV, performed well for all models simulated.

  14. When noisy neighbors are a blessing: analysis of gene expression noise identifies coregulated genes

    NARCIS (Netherlands)

    Junker, J.P.; van Oudenaarden, A.

    2012-01-01

    In this issue of Molecular Cell, Stewart-Ornstein et al. (2012) use systematic pair-wise correlation analysis of expression noise in a large number of yeast genes to identify clusters of functionally related genes and signaling pathways responsible for elevated noise.

  15. Identifying probable suicide clusters in wales using national mortality data.

    Directory of Open Access Journals (Sweden)

    Phillip Jones

    Full Text Available BACKGROUND: Up to 2% of suicides in young people may occur in clusters i.e., close together in time and space. In early 2008 unprecedented attention was given by national and international news media to a suspected suicide cluster among young people living in Bridgend, Wales. This paper investigates the strength of statistical evidence for this apparent cluster, its size, and temporal and geographical limits. METHODS AND FINDINGS: The analysis is based on official mortality statistics for Wales for 2000-2009 provided by the UK's Office for National Statistics (ONS. Temporo-spatial analysis was performed using Space Time Permutation Scan Statistics with SaTScan v9.1 for suicide deaths aged 15 and over, with a sub-group analysis focussing on cases aged 15-34 years. These analyses were conducted for deaths coded by ONS as: (i suicide or of undetermined intent (probable suicides and (ii for a combination of suicide, undetermined, and accidental poisoning and hanging (possible suicides. The temporo-spatial analysis did not identify any clusters of suicide or undetermined intent deaths (probable suicides. However, analysis of all deaths by suicide, undetermined intent, accidental poisoning and accidental hanging (possible suicides identified a temporo-spatial cluster (p = 0.029 involving 10 deaths amongst 15-34 year olds centred on the County Borough of Bridgend for the period 27(th December 2007 to 19(th February 2008. Less than 1% of possible suicides in younger people in Wales in the ten year period were identified as being cluster-related. CONCLUSIONS: There was a possible suicide cluster in young people in Bridgend between December 2007 and February 2008. This cluster was smaller, shorter in duration, and predominantly later than the phenomenon that was reported in national and international print media. Further investigation of factors leading to the onset and termination of this series of deaths, in particular the role of the media, is

  16. A 6-gene signature identifies four molecular subgroups of neuroblastoma

    Directory of Open Access Journals (Sweden)

    Kogner Per

    2011-04-01

    Full Text Available Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB; Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples. Four distinct clusters were identified by Principal Components Analysis (PCA in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.

  17. Lateral transfer of the lux gene cluster.

    Science.gov (United States)

    Kasai, Sabu; Okada, Kazuhisa; Hoshino, Akinori; Iida, Tetsuya; Honda, Takeshi

    2007-02-01

    The lux operon is an uncommon gene cluster. To find the pathway through which the operon has been transferred, we sequenced the operon and both flanking regions in four typical luminous species. In Vibrio cholerae NCIMB 41, a five-gene cluster, most genes of which were highly similar to orthologues present in Gram-positive bacteria, along with the lux operon, is inserted between VC1560 and VC1563, on chromosome 1. Because this entire five-gene cluster is present in Photorhabdus luminescens TT01, about 1.5 Mbp upstream of the operon, we deduced that the operon and the gene cluster were transferred from V. cholerae to an ancestor of Pr. luminescens. Because in both V. fischeri and Shewanella hanedai, luxR and luxI were found just upstream of the operon, we concluded that the operon was transferred from either species to the other. Because most of the genes flanking the operon were highly similar to orthologues present on chromosome 2 of vibrios, we speculated that the operon of most species is located on this chromosome. The undigested genomic DNAs of five luminous species were analysed by pulsed-field gel electrophoresis and Southern hybridization. In all the species except V. cholerae, the operons are located on chromosome 2.

  18. 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.

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

    Science.gov (United States)

    Brefort, Thomas; Tanaka, Shigeyuki; Neidig, Nina; Doehlemann, Gunther; Vincon, Volker; Kahmann, Regine

    2014-07-01

    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.

  20. Genome classification by gene distribution: An overlapping subspace clustering approach

    Directory of Open Access Journals (Sweden)

    Halgamuge Saman K

    2008-04-01

    Full Text Available Abstract Background Genomes of lower organisms have been observed with a large amount of horizontal gene transfers, which cause difficulties in their evolutionary study. Bacteriophage genomes are a typical example. One recent approach that addresses this problem is the unsupervised clustering of genomes based on gene order and genome position, which helps to reveal species relationships that may not be apparent from traditional phylogenetic methods. Results We propose the use of an overlapping subspace clustering algorithm for such genome classification problems. The advantage of subspace clustering over traditional clustering is that it can associate clusters with gene arrangement patterns, preserving genomic information in the clusters produced. Additionally, overlapping capability is desirable for the discovery of multiple conserved patterns within a single genome, such as those acquired from different species via horizontal gene transfers. The proposed method involves a novel strategy to vectorize genomes based on their gene distribution. A number of existing subspace clustering and biclustering algorithms were evaluated to identify the best framework upon which to develop our algorithm; we extended a generic subspace clustering algorithm called HARP to incorporate overlapping capability. The proposed algorithm was assessed and applied on bacteriophage genomes. The phage grouping results are consistent overall with the Phage Proteomic Tree and showed common genomic characteristics among the TP901-like, Sfi21-like and sk1-like phage groups. Among 441 phage genomes, we identified four significantly conserved distribution patterns structured by the terminase, portal, integrase, holin and lysin genes. We also observed a subgroup of Sfi21-like phages comprising a distinctive divergent genome organization and identified nine new phage members to the Sfi21-like genus: Staphylococcus 71, phiPVL108, Listeria A118, 2389, Lactobacillus phi AT3, A2

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

    Science.gov (United States)

    Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

    2013-01-02

    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 supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have 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.

  2. Ontology-Driven Co-clustering of Gene Expression Data

    Science.gov (United States)

    Cordero, Francesca; Pensa, Ruggero G.; Visconti, Alessia; Ienco, Dino; Botta, Marco

    The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to evaluate the data and to formulate new biological hypotheses. To this purpose, co-clustering techniques are widely used: these identify groups of genes that show similar activity patterns under a specific subset of the experimental conditions by measuring the similarity in expression within these groups. However, in many applications, distance metrics based only on expression levels fail in capturing biologically meaningful clusters.

  3. Identification and structural analysis of a novel snoRNA gene cluster from Arabidopsis thaliana

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A Z2 snoRNA gene cluster,consisting of four antisense snoRNA genes, was identified from Arabidopsis thaliana. The sequence and structural analysis showed that the Z2 snoRNA gene cluster might be transcribed as a polycistronic precursor from an upstream promoter, and the intergenic spacers of the gene cluster encode the 'hairpin' structures similar to the processing recognition signals of yeast Saccharomyces cerevisiae polycistronic snoRNA precursor. The results also revealed that plant snoRNA gene with multiple copies is a characteristic in common, and provides a good system for further revealing the transcription and expression mechanism of plant snoRNA gene cluster.

  4. A maize-specifically expressed gene cluster in Ustilago maydis.

    Science.gov (United States)

    Basse, Christoph W; Kolb, Sebastian; Kahmann, Regine

    2002-01-01

    The corn pathogen Ustilago maydis requires its host plant maize for development and completion of its sexual cycle. We have identified the fungal mig2-1 gene as being specifically expressed during this biotrophic stage. Intriguingly, mig2-1 is part of a gene cluster comprising five highly homologous and similarly regulated genes designated mig2-1 to mig2-5. Deletion analysis of the mig2-1 promoter provides evidence for negative and positive regulation. The predicted polypeptides of all five genes lack significant homologies to known genes but have characteristic N-terminal secretion sequences. The secretion signals of mig2-1 and mig2-5 were shown to be functional, and secretion of a full length Mig2-1-eGFP fusion protein to the extracellular space was demonstrated. The central domains of the Mig2 proteins are highly variable whereas the C-termini are strongly conserved and share a characteristic pattern of eight cysteine residues. The mig2 gene cluster was conserved in a wide collection of U. maydis strains. Interestingly, some U. maydis isolates from South America had lost the mig2-4 gene as a result of a homologous recombination event. Furthermore, the related Ustilago scitaminea strain, which is pathogenic on sugar cane, appears to lack the mig2 cluster. We describe a model of how the mig2 cluster might have evolved and discuss its possible role in governing host interaction.

  5. Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

    Science.gov (United States)

    Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

    2013-01-01

    Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

  6. Identification of the Scopularide Biosynthetic Gene Cluster in Scopulariopsis brevicaulis

    Directory of Open Access Journals (Sweden)

    Mie Bech Lukassen

    2015-07-01

    Full Text Available Scopularide A is a promising potent anticancer lipopeptide isolated from a marine derived Scopulariopsis brevicaulis strain. The compound consists of a reduced carbon chain (3-hydroxy-methyldecanoyl attached to five amino acids (glycine, l-valine, d-leucine, l-alanine, and l-phenylalanine. Using the newly sequenced S. brevicaulis genome we were able to identify the putative biosynthetic gene cluster using genetic information from the structurally related emericellamide A from Aspergillus nidulans and W493-B from Fusarium pseudograminearum. The scopularide A gene cluster includes a nonribosomal peptide synthetase (NRPS1, a polyketide synthase (PKS2, a CoA ligase, an acyltransferase, and a transcription factor. Homologous recombination was low in S. brevicaulis so the local transcription factor was integrated randomly under a constitutive promoter, which led to a three to four-fold increase in scopularide A production. This indirectly verifies the identity of the proposed biosynthetic gene cluster.

  7. Cluster Analysis of Gene Expression Data

    CERN Document Server

    Domany, E

    2002-01-01

    The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from a...

  8. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  9. 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.

  10. Coupled two-way clustering analysis of gene microarray data

    Science.gov (United States)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  11. 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...

  12. Identifying multiple influential spreaders by a heuristic clustering algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Bao, Zhong-Kui [School of Mathematical Science, Anhui University, Hefei 230601 (China); Liu, Jian-Guo [Data Science and Cloud Service Research Center, Shanghai University of Finance and Economics, Shanghai, 200133 (China); Zhang, Hai-Feng, E-mail: haifengzhang1978@gmail.com [School of Mathematical Science, Anhui University, Hefei 230601 (China); Department of Communication Engineering, North University of China, Taiyuan, Shan' xi 030051 (China)

    2017-03-18

    The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.

  13. An alanine tRNA gene cluster from Nephila clavipes.

    Science.gov (United States)

    Luciano, E; Candelas, G C

    1996-06-01

    We report the sequence of a 2.3-kb genomic DNA fragment from the orb-web spider, Nephila clavipes (Nc). The fragment contains four regions of high homology to tRNA(Ala). The members of this irregularly spaced cluster of genes are oriented in the same direction and have the same anticodon (GCA), but their sequence differs at several positions. Initiation and termination signals, as well as consensus intragenic promoter sequences characteristic of tRNA genes, have been identified in all genes. tRNA(Ala) are involved in the regulation of the fibroin synthesis in the large ampullate Nc glands.

  14. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

    Directory of Open Access Journals (Sweden)

    Jeban Ganesalingam

    Full Text Available BACKGROUND: Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS: Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS: The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001. CONCLUSION: The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

  15. Coordinated evolution of co-expressed gene clusters in the Drosophila transcriptome

    Directory of Open Access Journals (Sweden)

    Jones Corbin D

    2008-01-01

    Full Text Available Abstract Background Co-expression of genes that physically cluster together is a common characteristic of eukaryotic transcriptomes. This organization of transcriptomes suggests that coordinated evolution of gene expression for clustered genes may also be common. Clusters where expression evolution of each gene is not independent of their neighbors are important units for understanding transcriptome evolution. Results We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence. To summarize the correlation structure among genes in a chromosomal region, we analyzed the fraction of variation along the first principal component of the correlation matrix. We analyzed the correlation for blocks of consecutive genes to assess patterns of correlation that may be manifest at different scales of coordinated expression. We find that expression of physically clustered genes does evolve in a coordinated manner in many locations throughout the genome. Our analysis shows that relatively few of these clusters are near heterochromatin regions and that these clusters tend to be over-dispersed relative to the rest of the genome. This suggests that these clusters are not the byproduct of local gene clustering. We also analyzed the pattern of co-expression among neighboring genes within a single Drosophila species: D. simulans. For the co-expression clusters identified within this species, we find an under-representation of genes displaying a signature of recurrent adaptive amino acid evolution consistent with previous findings. However, clusters displaying co-evolution of expression among species are enriched for adaptively evolving genes. This finding points to a tie between adaptive sequence evolution and evolution of the transcriptome. Conclusion Our results demonstrate that co-evolution of expression in gene clusters is

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

    CERN Document Server

    H, Swathi

    2010-01-01

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

  17. Identifying prototypical components in behaviour using clustering algorithms.

    Directory of Open Access Journals (Sweden)

    Elke Braun

    Full Text Available Quantitative analysis of animal behaviour is a requirement to understand the task solving strategies of animals and the underlying control mechanisms. The identification of repeatedly occurring behavioural components is thereby a key element of a structured quantitative description. However, the complexity of most behaviours makes the identification of such behavioural components a challenging problem. We propose an automatic and objective approach for determining and evaluating prototypical behavioural components. Behavioural prototypes are identified using clustering algorithms and finally evaluated with respect to their ability to represent the whole behavioural data set. The prototypes allow for a meaningful segmentation of behavioural sequences. We applied our clustering approach to identify prototypical movements of the head of blowflies during cruising flight. The results confirm the previously established saccadic gaze strategy by the set of prototypes being divided into either predominantly translational or rotational movements, respectively. The prototypes reveal additional details about the saccadic and intersaccadic flight sections that could not be unravelled so far. Successful application of the proposed approach to behavioural data shows its ability to automatically identify prototypical behavioural components within a large and noisy database and to evaluate these with respect to their quality and stability. Hence, this approach might be applied to a broad range of behavioural and neural data obtained from different animals and in different contexts.

  18. Evolution and differential expression of a vertebrate vitellogenin gene cluster

    Directory of Open Access Journals (Sweden)

    Kongshaug Heidi

    2009-01-01

    Full Text Available Abstract Background The multiplicity or loss of the vitellogenin (vtg gene family in vertebrates has been argued to have broad implications for the mode of reproduction (placental or non-placental, cleavage pattern (meroblastic or holoblastic and character of the egg (pelagic or benthic. Earlier proposals for the existence of three forms of vertebrate vtgs present conflicting models for their origin and subsequent duplication. Results By integrating phylogenetics of novel vtg transcripts from old and modern teleosts with syntenic analyses of all available genomic variants of non-metatherian vertebrates we identify the gene orthologies between the Sarcopterygii (tetrapod branch and Actinopterygii (fish branch. We argue that the vertebrate vtg gene cluster originated in proto-chromosome m, but that vtg genes have subsequently duplicated and rearranged following whole genome duplications. Sequencing of a novel fourth vtg transcript in labrid species, and the presence of duplicated paralogs in certain model organisms supports the notion that lineage-specific gene duplications frequently occur in teleosts. The data show that the vtg gene cluster is more conserved between acanthomorph teleosts and tetrapods, than in ostariophysan teleosts such as the zebrafish. The differential expression of the labrid vtg genes are further consistent with the notion that neofunctionalized Aa-type vtgs are important determinants of the pelagic or benthic character of the eggs in acanthomorph teleosts. Conclusion The vertebrate vtg gene cluster existed prior to the separation of Sarcopterygii from Actinopterygii >450 million years ago, a period associated with the second round of whole genome duplication. The presence of higher copy numbers in a more highly expressed subcluster is particularly prevalent in teleosts. The differential expression and latent neofunctionalization of vtg genes in acanthomorph teleosts is an adaptive feature associated with oocyte hydration

  19. 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

  20. 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......, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally...

  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. Identification and characterization of a novel diterpene gene cluster in Aspergillus nidulans.

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    Kirsi Bromann

    Full Text Available Fungal secondary metabolites are a rich source of medically useful compounds due to their pharmaceutical and toxic properties. Sequencing of fungal genomes has revealed numerous secondary metabolite gene clusters, yet products of many of these biosynthetic pathways are unknown since the expression of the clustered genes usually remains silent in normal laboratory conditions. Therefore, to discover new metabolites, it is important to find ways to induce the expression of genes in these otherwise silent biosynthetic clusters. We discovered a novel secondary metabolite in Aspergillus nidulans by predicting a biosynthetic gene cluster with genomic mining. A Zn(II(2Cys(6-type transcription factor, PbcR, was identified, and its role as a pathway-specific activator for the predicted gene cluster was demonstrated. Overexpression of pbcR upregulated the transcription of seven genes in the identified cluster and led to the production of a diterpene compound, which was characterized with GC/MS as ent-pimara-8(14,15-diene. A change in morphology was also observed in the strains overexpressing pbcR. The activation of a cryptic gene cluster by overexpression of its putative Zn(II(2Cys(6-type transcription factor led to discovery of a novel secondary metabolite in Aspergillus nidulans. Quantitative real-time PCR and DNA array analysis allowed us to predict the borders of the biosynthetic gene cluster. Furthermore, we identified a novel fungal pimaradiene cyclase gene as well as genes encoding 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA reductase and a geranylgeranyl pyrophosphate (GGPP synthase. None of these genes have been previously implicated in the biosynthesis of terpenes in Aspergillus nidulans. These results identify the first Aspergillus nidulans diterpene gene cluster and suggest a biosynthetic pathway for ent-pimara-8(14,15-diene.

  3. Identification and Characterization of a Novel Diterpene Gene Cluster in Aspergillus nidulans

    Science.gov (United States)

    Bromann, Kirsi; Toivari, Mervi; Viljanen, Kaarina; Vuoristo, Anu; Ruohonen, Laura; Nakari-Setälä, Tiina

    2012-01-01

    Fungal secondary metabolites are a rich source of medically useful compounds due to their pharmaceutical and toxic properties. Sequencing of fungal genomes has revealed numerous secondary metabolite gene clusters, yet products of many of these biosynthetic pathways are unknown since the expression of the clustered genes usually remains silent in normal laboratory conditions. Therefore, to discover new metabolites, it is important to find ways to induce the expression of genes in these otherwise silent biosynthetic clusters. We discovered a novel secondary metabolite in Aspergillus nidulans by predicting a biosynthetic gene cluster with genomic mining. A Zn(II)2Cys6–type transcription factor, PbcR, was identified, and its role as a pathway-specific activator for the predicted gene cluster was demonstrated. Overexpression of pbcR upregulated the transcription of seven genes in the identified cluster and led to the production of a diterpene compound, which was characterized with GC/MS as ent-pimara-8(14),15-diene. A change in morphology was also observed in the strains overexpressing pbcR. The activation of a cryptic gene cluster by overexpression of its putative Zn(II)2Cys6–type transcription factor led to discovery of a novel secondary metabolite in Aspergillus nidulans. Quantitative real-time PCR and DNA array analysis allowed us to predict the borders of the biosynthetic gene cluster. Furthermore, we identified a novel fungal pimaradiene cyclase gene as well as genes encoding 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase and a geranylgeranyl pyrophosphate (GGPP) synthase. None of these genes have been previously implicated in the biosynthesis of terpenes in Aspergillus nidulans. These results identify the first Aspergillus nidulans diterpene gene cluster and suggest a biosynthetic pathway for ent-pimara-8(14),15-diene. PMID:22506079

  4. Functional Analysis of the Fusarielin Biosynthetic Gene Cluster

    Directory of Open Access Journals (Sweden)

    Aida Droce

    2016-12-01

    Full Text Available Fusarielins are polyketides with a decalin core produced by various species of Aspergillus and Fusarium. Although the responsible gene cluster has been identified, the biosynthetic pathway remains to be elucidated. In the present study, members of the gene cluster were deleted individually in a Fusarium graminearum strain overexpressing the local transcription factor. The results suggest that a trans-acting enoyl reductase (FSL5 assists the polyketide synthase FSL1 in biosynthesis of a polyketide product, which is released by hydrolysis by a trans-acting thioesterase (FSL2. Deletion of the epimerase (FSL3 resulted in accumulation of an unstable compound, which could be the released product. A novel compound, named prefusarielin, accumulated in the deletion mutant of the cytochrome P450 monooxygenase FSL4. Unlike the known fusarielins from Fusarium, this compound does not contain oxygenized decalin rings, suggesting that FSL4 is responsible for the oxygenation.

  5. The rise of operon-like gene clusters in plants.

    Science.gov (United States)

    Boycheva, Svetlana; Daviet, Laurent; Wolfender, Jean-Luc; Fitzpatrick, Teresa B

    2014-07-01

    Gene clusters are common features of prokaryotic genomes also present in eukaryotes. Most clustered genes known are involved in the biosynthesis of secondary metabolites. Although horizontal gene transfer is a primary source of prokaryotic gene cluster (operon) formation and has been reported to occur in eukaryotes, the predominant source of cluster formation in eukaryotes appears to arise de novo or through gene duplication followed by neo- and sub-functionalization or translocation. Here we aim to provide an overview of the current knowledge and open questions related to plant gene cluster functioning, assembly, and regulation. We also present potential research approaches and point out the benefits of a better understanding of gene clusters in plants for both fundamental and applied plant science.

  6. Gene expression profiling: can we identify the right target genes?

    Directory of Open Access Journals (Sweden)

    J. E. Loyd

    2008-12-01

    Full Text Available Gene expression profiling allows the simultaneous monitoring of the transcriptional behaviour of thousands of genes, which may potentially be involved in disease development. Several studies have been performed in idiopathic pulmonary fibrosis (IPF, which aim to define genetic links to the disease in an attempt to improve the current understanding of the underlying pathogenesis of the disease and target pathways for intervention. Expression profiling has shown a clear difference in gene expression between IPF and normal lung tissue, and has identified a wide range of candidate genes, including those known to encode for proteins involved in extracellular matrix formation and degradation, growth factors and chemokines. Recently, familial pulmonary fibrosis cohorts have been examined in an attempt to detect specific genetic mutations associated with IPF. To date, these studies have identified families in which IPF is associated with mutations in the gene encoding surfactant protein C, or with mutations in genes encoding components of telomerase. Although rare and clearly not responsible for the disease in all individuals, the nature of these mutations highlight the importance of the alveolar epithelium in disease pathogenesis and demonstrate the potential for gene expression profiling in helping to advance the current understanding of idiopathic pulmonary fibrosis.

  7. Identifying Reference Objects by Hierarchical Clustering in Java Environment

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    RAHUL SAHA

    2011-09-01

    Full Text Available Recently Java programming environment has become so popular. Java programming language is a language that is designed to be portable enough to be executed in wide range of computers ranging from cell phones to supercomputers. Computer programs written in Java are compiled into Java Byte code instructions that are suitable for execution by a Java Virtual Machine implementation. Java virtual Machine is commonly implemented in software by means of an interpreter for the Java Virtual Machine instruction set. As an object oriented language, Java utilizes the concept of objects. Our idea is to identify the candidate objects references in a Java environment through hierarchical cluster analysis using reference stack and execution stack.

  8. Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

    Science.gov (United States)

    Boccippio, Dennis J.

    2003-01-01

    It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description

  9. Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

    Science.gov (United States)

    Boccippio, Dennis J.

    2003-01-01

    It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description

  10. Identifying the magnetotail lobes with Cluster magnetometer data

    Science.gov (United States)

    Coxon, J. C.; Jackman, C. M.; Freeman, M. P.; Forsyth, C.; Rae, I. J.

    2016-02-01

    We describe a novel method for identifying times when a spacecraft is in Earth's magnetotail lobes solely using magnetometer data. We propose that lobe intervals can be well identified as times when the magnetic field is strong and relatively invariant, defined using thresholds in the magnitude of BX and the standard deviation σ of the magnetic field magnitude. Using data from the Cluster spacecraft at downtail distances greater than 8 RE during 2001-2009, we find that thresholds of 30 nT and 3.5 nT, respectively, optimize agreement with a previous, independently derived lobe identification method that used both magnetic and plasma data over the same interval. Specifically, our method has a moderately high accuracy (66%) and a low probability of false detection (11%) in comparison to the other method. Furthermore, our method identifies the lobe on many other occasions when the previous method was unable to make any identification and yields longer continuous intervals in the lobe than the previous method, with intervals at the 90th percentile being triple the length. Our method also allows for analyses of the lobes outside the time span of the previous method.

  11. Using Clustering Algorithms to Identify Brown Dwarf Characteristics

    Science.gov (United States)

    Choban, Caleb

    2016-06-01

    Brown dwarfs are stars that are not massive enough to sustain core hydrogen fusion, and thus fade and cool over time. The molecular composition of brown dwarf atmospheres can be determined by observing absorption features in their infrared spectrum, which can be quantified using spectral indices. Comparing these indices to one another, we can determine what kind of brown dwarf it is, and if it is young or metal-poor. We explored a new method for identifying these subgroups through the expectation-maximization machine learning clustering algorithm, which provides a quantitative and statistical way of identifying index pairs which separate rare populations. We specifically quantified two statistics, completeness and concentration, to identify the best index pairs. Starting with a training set, we defined selection regions for young, metal-poor and binary brown dwarfs, and tested these on a large sample of L dwarfs. We present the results of this analysis, and demonstrate that new objects in these classes can be found through these methods.

  12. Arrangement of the Clostridium baratii F7 toxin gene cluster with identification of a σ factor that recognizes the botulinum toxin gene cluster promoters.

    Science.gov (United States)

    Dover, Nir; Barash, Jason R; Burke, Julianne N; Hill, Karen K; Detter, John C; Arnon, Stephen S

    2014-01-01

    Botulinum neurotoxin (BoNT) is the most poisonous substances known and its eight toxin types (A to H) are distinguished by the inability of polyclonal antibodies that neutralize one toxin type to neutralize any of the other seven toxin types. Infant botulism, an intestinal toxemia orphan disease, is the most common form of human botulism in the United States. It results from swallowed spores of Clostridium botulinum (or rarely, neurotoxigenic Clostridium butyricum or Clostridium baratii) that germinate and temporarily colonize the lumen of the large intestine, where, as vegetative cells, they produce botulinum toxin. Botulinum neurotoxin is encoded by the bont gene that is part of a toxin gene cluster that includes several accessory genes. We sequenced for the first time the complete botulinum neurotoxin gene cluster of nonproteolytic C. baratii type F7. Like the type E and the nonproteolytic type F6 botulinum toxin gene clusters, the C. baratii type F7 had an orfX toxin gene cluster that lacked the regulatory botR gene which is found in proteolytic C. botulinum strains and codes for an alternative σ factor. In the absence of botR, we identified a putative alternative regulatory gene located upstream of the C. baratii type F7 toxin gene cluster. This putative regulatory gene codes for a predicted σ factor that contains DNA-binding-domain homologues to the DNA-binding domains both of BotR and of other members of the TcdR-related group 5 of the σ70 family that are involved in the regulation of toxin gene expression in clostridia. We showed that this TcdR-related protein in association with RNA polymerase core enzyme specifically binds to the C. baratii type F7 botulinum toxin gene cluster promoters. This TcdR-related protein may therefore be involved in regulating the expression of the genes of the botulinum toxin gene cluster in neurotoxigenic C. baratii.

  13. 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.

  14. AntiSMASH 4.0 - improvements in chemistry prediction and gene cluster boundary identification

    NARCIS (Netherlands)

    Blin, Kai; Wolf, Thomas; Chevrette, Marc G.; Lu, Xiaowen; Schwalen, Christopher J.; Kautsar, Satria A.; Suarez Duran, Hernando G.; Los Santos, De Emmanuel L.C.; Kim, Hyun Uk; Nave, Mariana; Dickschat, Jeroen S.; Mitchell, Douglas A.; Shelest, Ekaterina; Breitling, Rainer; Takano, Eriko; Lee, Sang Yup; Weber, Tilmann; Medema, Marnix H.

    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

  15. 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.

  16. Combination of meta-analysis and graph clustering to identify prognostic markers of ESCC

    Directory of Open Access Journals (Sweden)

    Hongyun Gao

    2012-01-01

    Full Text Available Esophageal squamous cell carcinoma (ESCC is one of the most malignant gastrointestinal cancers and occurs at a high frequency rate in China and other Asian countries. Recently, several molecular markers were identified for predicting ESCC. Notwithstanding, additional prognostic markers, with a clear understanding of their underlying roles, are still required. Through bioinformatics, a graph-clustering method by DPClus was used to detect co-expressed modules. The aim was to identify a set of discriminating genes that could be used for predicting ESCC through graph-clustering and GO-term analysis. The results showed that CXCL12, CYP2C9, TGM3, MAL, S100A9, EMP-1 and SPRR3 were highly associated with ESCC development. In our study, all their predicted roles were in line with previous reports, whereby the assumption that a combination of meta-analysis, graph-clustering and GO-term analysis is effective for both identifying differentially expressed genes, and reflecting on their functions in ESCC.

  17. Combination of meta-analysis and graph clustering to identify prognostic markers of ESCC.

    Science.gov (United States)

    Gao, Hongyun; Wang, Lishan; Cui, Shitao; Wang, Mingsong

    2012-04-01

    Esophageal squamous cell carcinoma (ESCC) is one of the most malignant gastrointestinal cancers and occurs at a high frequency rate in China and other Asian countries. Recently, several molecular markers were identified for predicting ESCC. Notwithstanding, additional prognostic markers, with a clear understanding of their underlying roles, are still required. Through bioinformatics, a graph-clustering method by DPClus was used to detect co-expressed modules. The aim was to identify a set of discriminating genes that could be used for predicting ESCC through graph-clustering and GO-term analysis. The results showed that CXCL12, CYP2C9, TGM3, MAL, S100A9, EMP-1 and SPRR3 were highly associated with ESCC development. In our study, all their predicted roles were in line with previous reports, whereby the assumption that a combination of meta-analysis, graph-clustering and GO-term analysis is effective for both identifying differentially expressed genes, and reflecting on their functions in ESCC.

  18. Psychophysiological responses to pain identify reproducible human clusters.

    Science.gov (United States)

    Farmer, Adam D; Coen, Steven J; Kano, Michiko; Paine, Peter A; Shwahdi, Mustafa; Jafari, Jafar; Kishor, Jessin; Worthen, Sian F; Rossiter, Holly E; Kumari, Veena; Williams, Steven C R; Brammer, Michael; Giampietro, Vincent P; Droney, Joanne; Riley, Julia; Furlong, Paul L; Knowles, Charles H; Lightman, Stafford L; Aziz, Qasim

    2013-11-01

    Pain is a ubiquitous yet highly variable experience. The psychophysiological and genetic factors responsible for this variability remain unresolved. We hypothesised the existence of distinct human pain clusters (PCs) composed of distinct psychophysiological and genetic profiles coupled with differences in the perception and the brain processing of pain. We studied 120 healthy subjects in whom the baseline personality and anxiety traits and the serotonin transporter-linked polymorphic region (5-HTTLPR) genotype were measured. Real-time autonomic nervous system parameters and serum cortisol were measured at baseline and after standardised visceral and somatic pain stimuli. Brain processing reactions to visceral pain were studied in 29 subjects using functional magnetic resonance imaging (fMRI). The reproducibility of the psychophysiological responses to pain was assessed at year. In group analysis, visceral and somatic pain caused an expected increase in sympathetic and cortisol responses and activated the pain matrix according to fMRI studies. However, using cluster analysis, we found 2 reproducible PCs: at baseline, PC1 had higher neuroticism/anxiety scores (P ≤ 0.01); greater sympathetic tone (Ppain, less stimulus was tolerated (P ≤ 0.01), and there was an increase in parasympathetic tone (P ≤ 0.05). The 5-HTTLPR short allele was over-represented (P ≤ 0.005). PC2 had the converse profile at baseline and during pain. Brain activity differed (P ≤ 0.001); greater activity occurred in the left frontal cortex in PC1, whereas PC2 showed greater activity in the right medial/frontal cortex and right anterior insula. In health, 2 distinct reproducible PCs exist in humans. In the future, PC characterization may help to identify subjects at risk for developing chronic pain and may reduce variability in brain imaging studies.

  19. Genetic characteristics of vancomycin resistance gene cluster in Enterococcus spp.

    Science.gov (United States)

    Chunhui, Chen; Xiaogang, Xu

    2015-05-01

    Vancomycin resistant enterococci has become an important nosocomial pathogen since it is discovered in late 1980s. The products, encoded by vancomycin resistant gene cluster in enterococci, catalyze the synthesis of peptidoglycan precursors with low affinity with glycopeptide antibiotics including vancomycin and teicoplanin and lead to resistance. These vancomycin resistant gene clusters are classified into nine types according to their gene sequences and organization, or D-Ala:D-Lac (VanA, VanB, VanD and VanM) and D-Ala:D-Ser (VanC, VanE, VanG, VanL and VanN) ligase gene clusters based on the differences of their encoded ligases. Moreover, these gene clusters are characterized by their different resistance levels and infection models. In this review, we summarize the classification, gene organization and infection model of vancomycin resistant gene cluster in Enterococcus spp.

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

    Directory of Open Access Journals (Sweden)

    J.JEBA EMILYN

    2010-12-01

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

  1. Diversity and evolution of MicroRNA gene clusters

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    microRNA(miRNA) gene clusters are a group of miRNA genes clustered within a proximal distance on a chromosome.Although a large number of miRNA clusters have been uncovered in animal and plant genomes,the functional consequences of this arrangement are still poorly understood.Located in a polycistron,the coexpressed miRNA clusters are pivotal in coordinately regulating multiple processes,including embryonic development,cell cycles and cell differentiation.In this review,based on recent progress,we discuss the genomic diversity of miRNA gene clusters,the coordination of expression and function of the clustered miRNAs,and the evolutionarily adaptive processes with gain and loss of the clustering miRNA genes mediated by duplication and transposition events.

  2. Diversity and evolution of MicroRNA gene clusters

    Institute of Scientific and Technical Information of China (English)

    ZHANG YanFeng; ZHANG Rui; SU Bing

    2009-01-01

    microRNA (miRNA) gene clusters are a group of miRNA genes clustered within a proximal distance on a chromosome. Although a large number of miRNA clusters have been uncovered in animal and plant genomes, the functional consequences of this arrangement are still poorly understood. Located in a polycistron, the coexpressed miRNA clusters are pivotal in coordinately regulating multiple processes, including embryonic development, cell cycles and cell differentiation. In this review, based on recent progress, we discuss the genomic diversity of miRNA gene clusters, the coordination of expression and function of the clustered miRNAs, and the evolutionarily adaptive processes with gain and loss of the clustering miRNA genes mediated by duplication and transposition events.

  3. RNA-seq analysis identifies an intricate regulatory network controlling cluster root development in white lupin

    Science.gov (United States)

    2014-01-01

    Background Highly adapted plant species are able to alter their root architecture to improve nutrient uptake and thrive in environments with limited nutrient supply. Cluster roots (CRs) are specialised structures of dense lateral roots formed by several plant species for the effective mining of nutrient rich soil patches through a combination of increased surface area and exudation of carboxylates. White lupin is becoming a model-species allowing for the discovery of gene networks involved in CR development. A greater understanding of the underlying molecular mechanisms driving these developmental processes is important for the generation of smarter plants for a world with diminishing resources to improve food security. Results RNA-seq analyses for three developmental stages of the CR formed under phosphorus-limited conditions and two of non-cluster roots have been performed for white lupin. In total 133,045,174 high-quality paired-end reads were used for a de novo assembly of the root transcriptome and merged with LAGI01 (Lupinus albus gene index) to generate an improved LAGI02 with 65,097 functionally annotated contigs. This was followed by comparative gene expression analysis. We show marked differences in the transcriptional response across the various cluster root stages to adjust to phosphate limitation by increasing uptake capacity and adjusting metabolic pathways. Several transcription factors such as PLT, SCR, PHB, PHV or AUX/IAA with a known role in the control of meristem activity and developmental processes show an increased expression in the tip of the CR. Genes involved in hormonal responses (PIN, LAX, YUC) and cell cycle control (CYCA/B, CDK) are also differentially expressed. In addition, we identify primary transcripts of miRNAs with established function in the root meristem. Conclusions Our gene expression analysis shows an intricate network of transcription factors and plant hormones controlling CR initiation and formation. In addition

  4. 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.

  5. Detecting Sequence Homology at the Gene Cluster Level with MultiGeneBlast

    NARCIS (Netherlands)

    Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Nowick, Katja

    2013-01-01

    The genes encoding many biomolecular systems and pathways are genomically organized in operons or gene clusters. With MultiGeneBlast, we provide a user-friendly and effective tool to perform homology searches with operons or gene clusters as basic units, instead of single genes. The contextualizatio

  6. Detecting Sequence Homology at the Gene Cluster Level with MultiGeneBlast

    NARCIS (Netherlands)

    Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Nowick, Katja

    The genes encoding many biomolecular systems and pathways are genomically organized in operons or gene clusters. With MultiGeneBlast, we provide a user-friendly and effective tool to perform homology searches with operons or gene clusters as basic units, instead of single genes. The

  7. Progeny Clustering: A Method to Identify Biological Phenotypes

    Science.gov (United States)

    Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

    2015-01-01

    Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

  8. Identifying phase synchronization clusters in spatially extended dynamical systems

    CERN Document Server

    Bialonski, Stephan; 10.1103/PhysRevE.74.051909

    2010-01-01

    We investigate two recently proposed multivariate time series analysis techniques that aim at detecting phase synchronization clusters in spatially extended, nonstationary systems with regard to field applications. The starting point of both techniques is a matrix whose entries are the mean phase coherence values measured between pairs of time series. The first method is a mean field approach which allows to define the strength of participation of a subsystem in a single synchronization cluster. The second method is based on an eigenvalue decomposition from which a participation index is derived that characterizes the degree of involvement of a subsystem within multiple synchronization clusters. Simulating multiple clusters within a lattice of coupled Lorenz oscillators we explore the limitations and pitfalls of both methods and demonstrate (a) that the mean field approach is relatively robust even in configurations where the single cluster assumption is not entirely fulfilled, and (b) that the eigenvalue dec...

  9. Identification and structural analysis of a novel snoRNA gene cluster from Arabidopsis thaliana

    Institute of Scientific and Technical Information of China (English)

    周惠; 孟清; 屈良鹄

    2000-01-01

    A 22 snoRNA gene cluster, consisting of four antisense snoRNA genes, was identified from Arabidopsis thaliana. The sequence and structural analysis showed that the 22 snoRNA gene cluster might be transcribed as a polycistronic precursor from an upstream promoter, and the in-tergenic spacers of the gene cluster encode the ’hairpin’ structures similar to the processing recognition signals of yeast Saccharomyces cerevisiae polycistronic snoRNA precursor. The results also revealed that plant snoRNA gene with multiple copies is a characteristic in common, and provides a good system for further revealing the transcription and expression mechanism of plant snoRNA gene cluster.

  10. A Nomadic Subtelomeric Disease Resistance Gene Cluster in Common Bean

    Science.gov (United States)

    The B4 resistance (R)-gene cluster, located in subtelomeric region of chromosome 4, is one of the largest clusters known in common bean (Phaseolus vulgaris, Pv). We sequenced 650 kb spanning this locus and annotated 97 genes, 26 of which correspond to Coiled-coil-Nucleotide-Binding-Site-Leucine-Rich...

  11. Simultaneous clustering of multiple gene expression and physical interaction datasets.

    Directory of Open Access Journals (Sweden)

    Manikandan Narayanan

    2010-04-01

    Full Text Available Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as coexpression networks summarizing correlations among the expression profiles of genes and physical networks describing protein-protein and protein-DNA interactions among genes or gene-products. Our algorithm provides an efficient solution to a well-defined problem of jointly clustering networks, using techniques that permit certain theoretical guarantees on the quality of the detected clustering relative to the optimal clustering. These guarantees coupled with an effective scaling heuristic and the flexibility to handle multiple heterogeneous networks make our method JointCluster an advance over earlier approaches. Simulation results showed JointCluster to be more robust than alternate methods in recovering clusters implanted in networks with high false positive rates. In systematic evaluation of JointCluster and some earlier approaches for combined analysis of the yeast physical network and two gene expression datasets under glucose and ethanol growth conditions, JointCluster discovers clusters that are more consistently enriched for various reference classes capturing different aspects of yeast biology or yield better coverage of the analysed genes. These robust clusters, which are supported across multiple genomic datasets and diverse reference classes, agree with known biology of yeast under these growth conditions, elucidate the genetic control of coordinated transcription, and enable functional predictions for a number of uncharacterized genes.

  12. Genes for iron-sulphur cluster assembly are targets of abiotic stress in rice, Oryza sativa.

    Science.gov (United States)

    Liang, Xuejiao; Qin, Lu; Liu, Peiwei; Wang, Meihuan; Ye, Hong

    2014-03-01

    Iron-sulphur (Fe-S) cluster assembly occurs in chloroplasts, mitochondria and cytosol, involving dozens of genes in higher plants. In this study, we have identified 41 putative Fe-S cluster assembly genes in rice (Oryza sativa) genome, and the expression of all genes was verified. To investigate the role of Fe-S cluster assembly as a metabolic pathway, we applied abiotic stresses to rice seedlings and analysed Fe-S cluster assembly gene expression by qRT-PCR. Our data showed that genes for Fe-S cluster assembly in chloroplasts of leaves are particularly sensitive to heavy metal treatments, and that Fe-S cluster assembly genes in roots were up-regulated in response to iron toxicity, oxidative stress and some heavy metal assault. The effect of each stress treatment on the Fe-S cluster assembly machinery demonstrated an unexpected tissue or organelle specificity, suggesting that the physiological relevance of the Fe-S cluster assembly is more complex than thought. Furthermore, our results may reveal potential candidate genes for molecular breeding of rice.

  13. Motif-independent de novo detection of secondary metabolite gene clusters-toward identification from filamentous fungi.

    Science.gov (United States)

    Umemura, Myco; Koike, Hideaki; Machida, Masayuki

    2015-01-01

    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.

  14. A putative gene cluster from a Lyngbya wollei bloom that encodes paralytic shellfish toxin biosynthesis.

    Directory of Open Access Journals (Sweden)

    Troco K Mihali

    Full Text Available Saxitoxin and its analogs cause the paralytic shellfish-poisoning syndrome, adversely affecting human health and coastal shellfish industries worldwide. Here we report the isolation, sequencing, annotation, and predicted pathway of the saxitoxin biosynthetic gene cluster in the cyanobacterium Lyngbya wollei. The gene cluster spans 36 kb and encodes enzymes for the biosynthesis and export of the toxins. The Lyngbya wollei saxitoxin gene cluster differs from previously identified saxitoxin clusters as it contains genes that are unique to this cluster, whereby the carbamoyltransferase is truncated and replaced by an acyltransferase, explaining the unique toxin profile presented by Lyngbya wollei. These findings will enable the creation of toxin probes, for water monitoring purposes, as well as proof-of-concept for the combinatorial biosynthesis of these natural occurring alkaloids for the production of novel, biologically active compounds.

  15. Sequencing, characterization, and gene expression analysis of the histidine decarboxylase gene cluster of Morganella morganii.

    Science.gov (United States)

    Ferrario, Chiara; Borgo, Francesca; de Las Rivas, Blanca; Muñoz, Rosario; Ricci, Giovanni; Fortina, Maria Grazia

    2014-03-01

    The histidine decarboxylase gene cluster of Morganella morganii DSM30146(T) was sequenced, and four open reading frames, named hdcT1, hdc, hdcT2, and hisRS were identified. Two putative histidine/histamine antiporters (hdcT1 and hdcT2) were located upstream and downstream the hdc gene, codifying a pyridoxal-P dependent histidine decarboxylase, and followed by hisRS gene encoding a histidyl-tRNA synthetase. This organization was comparable with the gene cluster of other known Gram negative bacteria, particularly with that of Klebsiella oxytoca. Recombinant Escherichia coli strains harboring plasmids carrying the M. morganii hdc gene were shown to overproduce histidine decarboxylase, after IPTG induction at 37 °C for 4 h. Quantitative RT-PCR experiments revealed the hdc and hisRS genes were highly induced under acidic and histidine-rich conditions. This work represents the first description and identification of the hdc-related genes in M. morganii. Results support the hypothesis that the histidine decarboxylation reaction in this prolific histamine producing species may play a role in acid survival. The knowledge of the role and the regulation of genes involved in histidine decarboxylation should improve the design of rational strategies to avoid toxic histamine production in foods.

  16. The biosynthetic gene cluster for the beta-lactam carbapenem thienamycin in Streptomyces cattleya.

    Science.gov (United States)

    Núñez, Luz Elena; Méndez, Carmen; Braña, Alfredo F; Blanco, Gloria; Salas, José A

    2003-04-01

    beta-lactam ring formation in carbapenem and clavam biosynthesis proceeds through an alternative mechanism to the biosynthetic pathway of classic beta-lactam antibiotics. This involves the participation of a beta-lactam synthetase. Using available information from beta-lactam synthetases, we generated a probe for the isolation of the thienamycin cluster from Streptomyces cattleya. Genes homologous to carbapenem and clavulanic acid biosynthetic genes have been identified. They would participate in early steps of thienamycin biosynthesis leading to the formation of the beta-lactam ring. Other genes necessary for the biosynthesis of thienamycin have also been identified in the cluster (methyltransferases, cysteinyl transferases, oxidoreductases, hydroxylase, etc.) together with two regulatory genes, genes involved in exportation and/or resistance, and a quorum sensing system. Involvement of the cluster in thienamycin biosynthesis was demonstrated by insertional inactivation of several genes generating thienamycin nonproducing mutants.

  17. Bioinformatics methods for identifying candidate disease genes

    NARCIS (Netherlands)

    Driel, M.A. van; Brunner, H.G.

    2006-01-01

    With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information i

  18. A rough set based rational clustering framework for determining correlated genes.

    Science.gov (United States)

    Jeyaswamidoss, Jeba Emilyn; Thangaraj, Kesavan; Ramar, Kadarkarai; Chitra, Muthusamy

    2016-06-01

    Cluster analysis plays a foremost role in identifying groups of genes that show similar behavior under a set of experimental conditions. Several clustering algorithms have been proposed for identifying gene behaviors and to understand their significance. The principal aim of this work is to develop an intelligent rough clustering technique, which will efficiently remove the irrelevant dimensions in a high-dimensional space and obtain appropriate meaningful clusters. This paper proposes a novel biclustering technique that is based on rough set theory. The proposed algorithm uses correlation coefficient as a similarity measure to simultaneously cluster both the rows and columns of a gene expression data matrix and mean squared residue to generate the initial biclusters. Furthermore, the biclusters are refined to form the lower and upper boundaries by determining the membership of the genes in the clusters using mean squared residue. The algorithm is illustrated with yeast gene expression data and the experiment proves the effectiveness of the method. The main advantage is that it overcomes the problem of selection of initial clusters and also the restriction of one object belonging to only one cluster by allowing overlapping of biclusters.

  19. Identification of certain cancer-mediating genes using Gaussian fuzzy cluster validity index

    Indian Academy of Sciences (India)

    Anupam Ghosh; Rajat K De

    2015-10-01

    In this article, we have used an index, called Gaussian fuzzy index (GFI), recently developed by the authors, based on the notion of fuzzy set theory, for validating the clusters obtained by a clustering algorithm applied on cancer gene expression data. GFI is then used for the identification of genes that have altered quite significantly from normal state to carcinogenic state with respect to their mRNA expression patterns. The effectiveness of the methodology has been demonstrated on three gene expression cancer datasets dealing with human lung, colon and leukemia. The performance of GFI is compared with 19 exiting cluster validity indices. The results are appropriately validated biologically and statistically. In this context, we have used biochemical pathways, -value statistics of GO attributes, -test and -score for the validation of the results. It has been reported that GFI is capable of identifying high-quality enriched clusters of genes, and thereby is able to select more cancer-mediating genes.

  20. Mining Bacterial Genomes for Secondary Metabolite Gene Clusters.

    Science.gov (United States)

    Adamek, Martina; Spohn, Marius; Stegmann, Evi; Ziemert, Nadine

    2017-01-01

    With the emergence of bacterial resistance against frequently used antibiotics, novel antibacterial compounds are urgently needed. Traditional bioactivity-guided drug discovery strategies involve laborious screening efforts and display high rediscovery rates. With the progress in next generation sequencing methods and the knowledge that the majority of antibiotics in clinical use are produced as secondary metabolites by bacteria, mining bacterial genomes for secondary metabolites with antimicrobial activity is a promising approach, which can guide a more time and cost-effective identification of novel compounds. However, what sounds easy to accomplish, comes with several challenges. To date, several tools for the prediction of secondary metabolite gene clusters are available, some of which are based on the detection of signature genes, while others are searching for specific patterns in gene content or regulation.Apart from the mere identification of gene clusters, several other factors such as determining cluster boundaries and assessing the novelty of the detected cluster are important. For this purpose, comparison of the predicted secondary metabolite genes with different cluster and compound databases is necessary. Furthermore, it is advisable to classify detected clusters into gene cluster families. So far, there is no standardized procedure for genome mining; however, different approaches to overcome all of these challenges exist and are addressed in this chapter. We give practical guidance on the workflow for secondary metabolite gene cluster identification, which includes the determination of gene cluster boundaries, addresses problems occurring with the use of draft genomes, and gives an outlook on the different methods for gene cluster classification. Based on comprehensible examples a protocol is set, which should enable the readers to mine their own genome data for interesting secondary metabolites.

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

    Science.gov (United States)

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

    2015-06-01

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

  2. Clostridium botulinum strain Af84 contains three neurotoxin gene clusters: bont/A2, bont/F4 and bont/F5.

    Directory of Open Access Journals (Sweden)

    Nir Dover

    Full Text Available Sanger and shotgun sequencing of Clostridium botulinum strain Af84 type Af and its botulinum neurotoxin gene (bont clusters identified the presence of three bont gene clusters rather than the expected two. The three toxin gene clusters consisted of bont subtypes A2, F4 and F5. The bont/A2 and bont/F4 gene clusters were located within the chromosome (the latter in a novel location, while the bont/F5 toxin gene cluster was located within a large 246 kb plasmid. These findings are the first identification of a C. botulinum strain that contains three botulinum neurotoxin gene clusters.

  3. Cancer therapeutic target genes identified on chromosome 20q

    Directory of Open Access Journals (Sweden)

    Editorial Office

    2016-08-01

    , Snijders and Mao described that and “when the selection pressure is removed, amplifications are not maintained and eventually disappear. Thus, amplifications focus on those genes that are important for tumor development,” they said. Their analysis showed that, as tumorous cells progress toward malignancy, the DNA copy number plays a major role in the mechanism of increased expression levels for the 18-gene signature on chromosome 20q. “Strong associations between the DNA copy number and gene expression were observed in the majority of tumor types,” the researchers said. “For example, the RAE1 expression was found to be significantly associated with DNA copy number in 20 tumor types,” the study reported. “Elevated DNA copy numbers of MMP9 and SULF2 were associated with increased gene expressions in only two and seven tumor types, respectively,” it added. With their integrated multi-omics analysis of genes on chromosome 20q, Snijders and Mao believed that the 18-gene signature could become new molecular targets for cancer therapy. “Gene ontology analysis revealed significant enrichment of cell cycle and mitosis-related biological processes in our 18-gene, suggesting that a cluster of functionally related genes localize to chromosome 20q,” they said. The identification of good targets such as theirs is a critical step for the development of targeted therapies for cancer treatment, according to the researchers. Microarray and next generation sequencing technologies have become invaluable tools in cataloging genomic abnormalities in human cancers and identifying new potential therapeutic targets, in addition to the availability of large cancer genomic data sets which allows for unbiased approaches to identify genes that are important in tumor progression, the research study noted. “Here, we aggregated available cancer databases to identify cancer driver genes across tumor types by combining gene transcript and DNA copy number across chromosome 20q to

  4. Stick-slip behavior identified in helium cluster growth in the subsurface of tungsten: effects of cluster depth

    Science.gov (United States)

    Wang, Jinlong; Niu, Liang-Liang; Shu, Xiaolin; Zhang, Ying

    2015-10-01

    We have performed a molecular dynamics study on the growth of helium (He) clusters in the subsurface of tungsten (W) (1 0 0) at 300 K, focusing on the role of cluster depth. Irregular ‘stick-slip’ behavior exhibited during the evolution of the He cluster growth is identified, which is due to the combined effects of the continuous cluster growth and the loop punching induced pressure relief. We demonstrate that the He cluster grows via trap-mutation and loop punching mechanisms. Initially, the self-interstitial atom SIA clusters are almost always attached to the He cluster; while they are instantly emitted to the surface once a critical cluster pressure is reached. The repetition of this process results in the He cluster approaching the surface via a ‘stop-and-go’ manner and the formation of surface adatom islands (surface roughening), ultimately leading to cluster bursting and He escape. We reveal that, for the Nth loop punching event, the critical size of the He cluster to trigger loop punching and the size of the emitted SIA clusters are correspondingly increased with the increasing initial cluster depth. We tentatively attribute the observed depth effects to the lower formation energies of Frenkel pairs and the greatly reduced barriers for loop punching in the stress field of the W subsurface. In addition, some intriguing features emerge, such as the morphological transformation of the He cluster from ‘platelet-like’ to spherical, to ellipsoidal with a ‘bullet-like’ tip, and finally to a ‘bottle-like’ shape after cluster rupture.

  5. Bioinformatics methods for identifying candidate disease genes

    Directory of Open Access Journals (Sweden)

    van Driel Marc A

    2006-06-01

    Full Text Available Abstract With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies.

  6. clusterProfiler: an R package for comparing biological themes among gene clusters.

    Science.gov (United States)

    Yu, Guangchuang; Wang, Li-Gen; Han, Yanyan; He, Qing-Yu

    2012-05-01

    Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

  7. 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......DNA arrays have been a rich source of data for the study of genomic expression of a wide variety of biological systems. Gene clustering is one of the paradigms quite used to assess the significance of a gene (or group of genes). However, most of the gene clustering techniques are applied to c...... 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...

  8. Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

    Science.gov (United States)

    Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

    2017-11-01

    Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two.

  9. Identifying multiple influential spreaders by a heuristic clustering algorithm

    Science.gov (United States)

    Bao, Zhong-Kui; Liu, Jian-Guo; Zhang, Hai-Feng

    2017-03-01

    The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very "negligible". Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant.

  10. 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.

  11. 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.

  12. Identifying robust clusters and multi-community nodes by combining top-down and bottom-up approaches to clustering

    CERN Document Server

    Gaiteri, Chris; Szymanski, Boleslaw; Kuzmin, Konstantin; Xie, Jierui; Lee, Changkyu; Blanche, Timothy; Neto, Elias Chaibub; Huang, Su-Chun; Grabowski, Thomas; Madhyastha, Tara; Komashko, Vitalina

    2015-01-01

    Biological functions are often realized by groups of interacting molecules or cells. Membership in these groups may overlap when molecules or cells are reused in multiple functions. Traditional clustering methods assign each component to one group. Noisy measurements are common in high-throughput biological datasets. These two limitations reduce our ability to accurately define clusters in biological datasets and to interpret their biological functions. To address these limitations, we designed an algorithm called SpeakEasy, which detects overlapping or non-overlapping communities in biological networks. Input to SpeakEasy can be physical networks, such as molecular interactions, or inferred networks, such as gene coexpression networks. The networks can be directed or undirected, and may contain negative links. SpeakEasy combines traditional bottom-up and top-down approaches to clustering, by creating competition between clusters. Nodes that oscillate between multiple clusters in this competition are classifi...

  13. Gene prioritization and clustering by multi-view text mining.

    Science.gov (United States)

    Yu, Shi; Tranchevent, Leon-Charles; De Moor, Bart; Moreau, Yves

    2010-01-14

    Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. We present a multi-view approach to retrieve biomedical knowledge using different controlled vocabularies. These controlled vocabularies are selected on the basis of nine well-known bio-ontologies and are applied to index the vast amounts of gene-based free-text information available in the MEDLINE repository. The text mining result specified by a vocabulary is considered as a view and the obtained multiple views are integrated by multi-source learning algorithms. We investigate the effect of integration in two fundamental computational disease gene identification tasks: gene prioritization and gene clustering. The performance of the proposed approach is systematically evaluated and compared on real benchmark data sets. In both tasks, the multi-view approach demonstrates significantly better performance than other comparing methods. In practical research, the relevance of specific vocabulary pertaining to the task is usually unknown. In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification.

  14. 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

    2015-01-01

    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.

  15. 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.

  16. Identifying novel genes contributing to asthma pathogenesis

    NARCIS (Netherlands)

    Holloway, John W.; Koppelman, Gerard H.

    2007-01-01

    Purpose of review To illustrate recent examples of novel asthma genes such as those encoding G-protein-coupled receptor for asthma susceptibility, filaggrin and tenascin-C, and to describe the process that is needed to translate these findings to the clinic. Recent findings Many hundreds of studies

  17. Recurring cluster and operon assembly for Phenylacetate degradation genes

    Directory of Open Access Journals (Sweden)

    McInerney James O

    2009-02-01

    Full Text Available Abstract Background A large number of theories have been advanced to explain why genes involved in the same biochemical processes are often co-located in genomes. Most of these theories have been dismissed because empirical data do not match the expectations of the models. In this work we test the hypothesis that cluster formation is most likely due to a selective pressure to gradually co-localise protein products and that operon formation is not an inevitable conclusion of the process. Results We have selected an exemplar well-characterised biochemical pathway, the phenylacetate degradation pathway, and we show that its complex history is only compatible with a model where a selective advantage accrues from moving genes closer together. This selective pressure is likely to be reasonably weak and only twice in our dataset of 102 genomes do we see independent formation of a complete cluster containing all the catabolic genes in the pathway. Additionally, de novo clustering of genes clearly occurs repeatedly, even though recombination should result in the random dispersal of such genes in their respective genomes. Interspecies gene transfer has frequently replaced in situ copies of genes resulting in clusters that have similar content but very different evolutionary histories. Conclusion Our model for cluster formation in prokaryotes, therefore, consists of a two-stage selection process. The first stage is selection to move genes closer together, either because of macromolecular crowding, chromatin relaxation or transcriptional regulation pressure. This proximity opportunity sets up a separate selection for co-transcription.

  18. 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

    2003-02-01

    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.

  19. 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...

  20. A gene cluster for amylovoran synthesis in Erwinia amylovora: characterization and relationship to cps genes in Erwinia stewartii.

    Science.gov (United States)

    Bernhard, F; Coplin, D L; Geider, K

    1993-05-01

    A large ams gene cluster required for production of the acidic extracellular polysaccharide (EPS) amylovoran by the fire blight pathogen Erwinia amylovora was cloned. Tn5 mutagenesis and gene replacement were used to construct chromosomal ams mutants. Five complementation groups, essential for amylovoran synthesis and virulence in E. amylovora, were identified and designated ams A-E. The ams gene cluster is about 7 kb in size and functionally equivalent to the cps gene cluster involved in EPS synthesis by the related pathogen Erwinia stewartii. Mucoidy and virulence were restored to E. stewartii mutants in four cps complementation groups by the cloned E. amylovora ams genes. Conversely, the E. stewartii cps gene cluster was able to complement mutations in E. amylovora ams genes. Correspondence was found between the amsA-E complementation groups and the cpsB-D region, but the arrangement of the genes appears to be different. EPS production and virulence were also restored to E. amylovora amsE and E. stewartii cpsD mutants by clones containing the Rhizobium meliloti exo A gene.

  1. Phylogeny of the Insect Homeobox Gene (Hox) Cluster

    Institute of Scientific and Technical Information of China (English)

    Sangeeta Dhawan; K. P. Gopinathan

    2005-01-01

    The homeobox (Hox) genes form an evolutionarily conserved family encoding transcription factors that play major roles in segmental identity and organ specification across species. The canonical grouping of Hox genes present in the HOM-C cluster of Drosophila or related clusters in other organisms includes eight "typical" genes,which are localized in the order labial (lab), proboscipedia (pb), Deformed (Dfd),Sex combs reduced ( Scr), Antennapedia (Antp), Ultrabithorax (Ubx), abdominalA (abdA), and AbdominalB (AbdB). The members of Hox cluster are expressed in a distinct anterior to posterior order in the embryo. Analysis of the relatedness of different members of the Hox gene cluster to each other in four evolutionarily diverse insect taxa revealed that the loci pb/Dfd and AbdB, which are farthest apart in linkage, had a high degree of evolutionary relatedness, indicating that pb/Dfd type anterior genes and AbdB are closest to the ancestral anterior and posterior Hox genes, respectively. The greater relatedness of other posterior genes Ubx and abdA to the more anterior genes such as Antp and Scr suggested that they arose by gene duplications in the more anterior members rather than the posterior AbdB.

  2. Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

    Science.gov (United States)

    Chan, Julia Y. K.; Bauer, Christopher F.

    2014-01-01

    The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

  3. Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

    Science.gov (United States)

    Chan, Julia Y. K.; Bauer, Christopher F.

    2014-01-01

    The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

  4. 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).

  5. 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

  6. Secondary metabolic gene clusters: evolutionary toolkits for chemical innovation.

    Science.gov (United States)

    Osbourn, Anne

    2010-10-01

    Microbes and plants produce a huge array of secondary metabolites that have important ecological functions. These molecules have long been exploited in medicine as antibiotics, anticancer and anti-infective agents and for a wide range of other applications. Gene clusters for secondary metabolic pathways are common in bacteria and filamentous fungi, and examples have now been discovered in plants. Here, current knowledge of gene clusters across the kingdoms is evaluated with the aim of trying to understand the rules behind cluster existence and evolution. Such knowledge will be crucial in learning how to activate the enormous number of 'silent' gene clusters being revealed by whole-genome sequencing and hence in making available a wealth of novel compounds for evaluation as drug leads and other bioactives. It could also facilitate the development of crop plants with enhanced pest or disease resistance, improved nutritional qualities and/or elevated levels of high-value products.

  7. 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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles...... for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying...

  9. Identification and comparative analyses of Siamois cluster genes in Xenopus laevis and tropicalis.

    Science.gov (United States)

    Haramoto, Yoshikazu; Saijyo, Tomohito; Tanaka, Toshiaki; Furuno, Nobuaki; Suzuki, Atsushi; Ito, Yuzuru; Kondo, Mariko; Taira, Masanori; Takahashi, Shuji

    2017-06-15

    Two siamois-related homeobox genes siamois (sia1) and twin (sia2), have been reported in Xenopus laevis. These genes are expressed in the blastula chordin- and noggin-expressing (BCNE) center and the Nieuwkoop center, and have complete secondary axis-inducing activity when over-expressed on the ventral side of the embryo. Using whole genome sequences of X. tropicalis and X. laevis, we identified two additional siamois-related genes, which are tandemly duplicated near sia1 and sia2 to form the siamois gene cluster. Four siamois genes in X. tropicalis are transcribed at blastula to gastrula stages. In X. laevis, the siamois gene cluster is present on both homeologous chromosomes, XLA3L and XLA3S. Transcripts from seven siamois genes (three on XLA3L and four on XLA3S) in X. laevis were detected at blastula to gastrula stages. A transcribed gene, sia1p. S, encodes an inactive protein without a homeodomain. When over-expressed ventrally, all siamois-related genes tested in this study except for sia1p. S induced a complete secondary axis, indicating that X. tropicalis and X. laevis have four and six active siamois-related genes, respectively. Of note, each gene required different amounts of mRNA for full activity. These results suggest the possibility that siamois cluster genes have functional redundancy to endow robustness and quickness to organizer formation in Xenopus species. Copyright © 2017. Published by Elsevier Inc.

  10. Characterization and biological role of the O-polysaccharide gene cluster of Yersinia enterocolitica serotype O : 9

    DEFF Research Database (Denmark)

    Skurnik, Mikael; Biedzka-Sarek, Marta; Lubeck, Peter S.

    2007-01-01

    as an attachment site for both the outer core (OC) hexasaccharide and the O-polysaccharide (OPS; a homopolymer of N-formylperosamine). In this work, we cloned the OPS gene cluster of O:9 and identified 12 genes organized into four operons upstream of the gnd gene. Ten genes were predicted to encode...... glycosyltransferases, the ATP-binding cassette polysaccharide translocators, or enzymes required for the biosynthesis of GDP-N-formylperosamine. The two remaining genes within the OPS gene cluster, galF and galU, were not ascribed a clear function in OPS biosynthesis; however, the latter gene appeared to be essential...

  11. 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.

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

    Science.gov (United States)

    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

    1989-02-01

    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 nifH, nifD, nifK, nifT, nifY, nifE, nifN, nifX, nifU, nifS, nifV, nifW, nifZ, nifM, and nifF. Although there are significant spatial differences, the identified A. vinelandii nif-specific genes have the same sequential arrangement as the corresponding nif-specific genes from K. pneumoniae. Twelve other potential genes whose expression could be subject to nif-specific regulation were also found interspersed among the identified nif-specific genes. These potential genes do not encode products that are structurally related to the identified nif-specific gene products. Eleven potential nif-specific promoters were identified within the major nif cluster, and nine of these are preceded by an appropriate upstream activator sequence. A + T-rich regions were identified between 8 of the 11 proposed nif promoter sequences and their upstream activator sequences. Site-directed deletion-and-insertion mutagenesis was used to establish a genetic map of the major nif cluster.

  13. Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

    Science.gov (United States)

    Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

    2014-12-01

    Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

  14. 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

  15. An improved algorithm for clustering gene expression data.

    Science.gov (United States)

    Bandyopadhyay, Sanghamitra; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2007-11-01

    Recent advancements in microarray technology allows simultaneous monitoring of the expression levels of a large number of genes over different time points. Clustering is an important tool for analyzing such microarray data, typical properties of which are its inherent uncertainty, noise and imprecision. In this article, a two-stage clustering algorithm, which employs a recently proposed variable string length genetic scheme and a multiobjective genetic clustering algorithm, is proposed. It is based on the novel concept of points having significant membership to multiple classes. An iterated version of the well-known Fuzzy C-Means is also utilized for clustering. The significant superiority of the proposed two-stage clustering algorithm as compared to the average linkage method, Self Organizing Map (SOM) and a recently developed weighted Chinese restaurant-based clustering method (CRC), widely used methods for clustering gene expression data, is established on a variety of artificial and publicly available real life data sets. The biological relevance of the clustering solutions are also analyzed.

  16. Interpolation based consensus clustering for gene expression time series.

    Science.gov (United States)

    Chiu, Tai-Yu; Hsu, Ting-Chieh; Yen, Chia-Cheng; Wang, Jia-Shung

    2015-04-16

    Unsupervised analyses such as clustering are the essential tools required to interpret time-series expression data from microarrays. Several clustering algorithms have been developed to analyze gene expression data. Early methods such as k-means, hierarchical clustering, and self-organizing maps are popular for their simplicity. However, because of noise and uncertainty of measurement, these common algorithms have low accuracy. Moreover, because gene expression is a temporal process, the relationship between successive time points should be considered in the analyses. In addition, biological processes are generally continuous; therefore, the datasets collected from time series experiments are often found to have an insufficient number of data points and, as a result, compensation for missing data can also be an issue. An affinity propagation-based clustering algorithm for time-series gene expression data is proposed. The algorithm explores the relationship between genes using a sliding-window mechanism to extract a large number of features. In addition, the time-course datasets are resampled with spline interpolation to predict the unobserved values. Finally, a consensus process is applied to enhance the robustness of the method. Some real gene expression datasets were analyzed to demonstrate the accuracy and efficiency of the algorithm. The proposed algorithm has benefitted from the use of cubic B-splines interpolation, sliding-window, affinity propagation, gene relativity graph, and a consensus process, and, as a result, provides both appropriate and effective clustering of time-series gene expression data. The proposed method was tested with gene expression data from the Yeast galactose dataset, the Yeast cell-cycle dataset (Y5), and the Yeast sporulation dataset, and the results illustrated the relationships between the expressed genes, which may give some insights into the biological processes involved.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

    Directory of Open Access Journals (Sweden)

    Victor M. Bii

    2016-10-01

    Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.

  19. Whole Genome Sequencing Demonstrates Limited Transmission within Identified Mycobacterium tuberculosis Clusters in New South Wales, Australia

    Science.gov (United States)

    Gurjav, Ulziijargal; Outhred, Alexander C.; Jelfs, Peter; McCallum, Nadine; Wang, Qinning; Hill-Cawthorne, Grant A.; Marais, Ben J.; Sintchenko, Vitali

    2016-01-01

    Australia has a low tuberculosis incidence rate with most cases occurring among recent immigrants. Given suboptimal cluster resolution achieved with 24-locus mycobacterium interspersed repetitive unit (MIRU-24) genotyping, the added value of whole genome sequencing was explored. MIRU-24 profiles of all Mycobacterium tuberculosis culture-confirmed tuberculosis cases diagnosed between 2009 and 2013 in New South Wales (NSW), Australia, were examined and clusters identified. The relatedness of cases within the largest MIRU-24 clusters was assessed using whole genome sequencing and phylogenetic analyses. Of 1841 culture-confirmed TB cases, 91.9% (1692/1841) had complete demographic and genotyping data. East-African Indian (474; 28.0%) and Beijing (470; 27.8%) lineage strains predominated. The overall rate of MIRU-24 clustering was 20.1% (340/1692) and was highest among Beijing lineage strains (35.7%; 168/470). One Beijing and three East-African Indian (EAI) clonal complexes were responsible for the majority of observed clusters. Whole genome sequencing of the 4 largest clusters (30 isolates) demonstrated diverse single nucleotide polymorphisms (SNPs) within identified clusters. All sequenced EAI strains and 70% of Beijing lineage strains clustered by MIRU-24 typing demonstrated distinct SNP profiles. The superior resolution provided by whole genome sequencing demonstrated limited M. tuberculosis transmission within NSW, even within identified MIRU-24 clusters. Routine whole genome sequencing could provide valuable public health guidance in low burden settings. PMID:27737005

  20. Identification of the Fucose Synthetase Gene in the Colanic Acid Gene Cluster of Escherichia coli K-12

    OpenAIRE

    Andrianopoulos, Kanella; Wang, Lei; Reeves, Peter R.

    1998-01-01

    GDP–l-fucose, the substrate for fucosyltransferases for addition of fucose to polysaccharides or glycoproteins in both procaryotes and eucaryotes, is made from GDP–d-mannose. l-Fucose is a component of bacterial surface antigens, including the extracellular polysaccharide colanic acid produced by most Escherichia coli strains. We previously sequenced the E. coli colanic acid gene cluster and identified one of the GDP–l-fucose biosynthetic pathway genes, gmd. We report here the identification ...

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

    African Journals Online (AJOL)

    adriana

    2013-12-04

    Dec 4, 2013 ... identifying all the components of a single biological system is within our means; however, assigning ... discovery of new candidate genes/QTLs and/or to assign ... identify putative genes involved in their genetic control .... for adaptation to different environments. ..... provides insights into fleshy fruit evolution.

  2. Unique nucleotide polymorphism of ankyrin gene cluster in Arabidopsis

    Indian Academy of Sciences (India)

    Jianchang Du; Xingna Wang; Mingsheng Zhang; Dacheng Tian; Yong-Hua Yang

    2007-01-01

    The ankyrin (ANK) gene cluster is a part of a multigene family encoding ANK transmembrane proteins in Arabidopsis thaliana, and plays an important role in protein–protein interactions and in signal pathways. In contrast to other regions of a genome, the ANK gene cluster exhibits an extremely high level of DNA polymorphism in an ∼5-kb region, without apparent decay. Phylogenetic analysis detects two clear, deeply differentiated haplotypes (dimorphism). The divergence between haplotypes of accession Col-0 and Ler-0 (Hap-C and Hap-L) is estimated to be 10.7%, approximately equal to the 10.5% average divergence between A. thaliana and A. lyrata. Sequence comparisons for the ANK gene cluster homologues in Col-0 indicate that the members evolve independently, and that the similarity among paralogues is lower than between alleles. Very little intralocus recombination or gene conversion is detected in ANK regions. All these characteristics of the ANK gene cluster are consistent with a tandem gene duplication and birth-and-death process. The possible mechanisms for and implications of this elevated nucleotide variation are also discussed, including the suggestion of balancing selection.

  3. Identifying robust communities and multi-community nodes by combining top-down and bottom-up approaches to clustering.

    Science.gov (United States)

    Gaiteri, Chris; Chen, Mingming; Szymanski, Boleslaw; Kuzmin, Konstantin; Xie, Jierui; Lee, Changkyu; Blanche, Timothy; Chaibub Neto, Elias; Huang, Su-Chun; Grabowski, Thomas; Madhyastha, Tara; Komashko, Vitalina

    2015-11-09

    Biological functions are carried out by groups of interacting molecules, cells or tissues, known as communities. Membership in these communities may overlap when biological components are involved in multiple functions. However, traditional clustering methods detect non-overlapping communities. These detected communities may also be unstable and difficult to replicate, because traditional methods are sensitive to noise and parameter settings. These aspects of traditional clustering methods limit our ability to detect biological communities, and therefore our ability to understand biological functions. To address these limitations and detect robust overlapping biological communities, we propose an unorthodox clustering method called SpeakEasy which identifies communities using top-down and bottom-up approaches simultaneously. Specifically, nodes join communities based on their local connections, as well as global information about the network structure. This method can quantify the stability of each community, automatically identify the number of communities, and quickly cluster networks with hundreds of thousands of nodes. SpeakEasy shows top performance on synthetic clustering benchmarks and accurately identifies meaningful biological communities in a range of datasets, including: gene microarrays, protein interactions, sorted cell populations, electrophysiology and fMRI brain imaging.

  4. 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

  5. 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.

  6. Digital gene expression profiling of flax (Linum usitatissimum L.) stem peel identifies genes enriched in fiber-bearing phloem tissue.

    Science.gov (United States)

    Guo, Yuan; Qiu, Caisheng; Long, Songhua; Chen, Ping; Hao, Dongmei; Preisner, Marta; Wang, Hui; Wang, Yufu

    2017-08-30

    To better understand the molecular mechanisms and gene expression characteristics associated with development of bast fiber cell within flax stem phloem, the gene expression profiling of flax stem peels and leaves were screened, using Illumina's Digital Gene Expression (DGE) analysis. Four DGE libraries (2 for stem peel and 2 for leaf), ranging from 6.7 to 9.2 million clean reads were obtained, which produced 7.0 million and 6.8 million mapped reads for flax stem peel and leave, respectively. By differential gene expression analysis, a total of 975 genes, of which 708 (73%) genes have protein-coding annotation, were identified as phloem enriched genes putatively involved in the processes of polysaccharide and cell wall metabolism. Differential expression genes (DEGs) was validated using quantitative RT-PCR, the expression pattern of all nine genes determined by qRT-PCR fitted in well with that obtained by sequencing analysis. Cluster and Gene Ontology (GO) analysis revealed that a large number of genes related to metabolic process, catalytic activity and binding category were expressed predominantly in the stem peels. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the phloem enriched genes suggested approximately 111 biological pathways. The large number of genes and pathways produced from DGE sequencing will expand our understanding of the complex molecular and cellular events in flax bast fiber development and provide a foundation for future studies on fiber development in other bast fiber crops. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Using biologically interrelated experiments to identify pathway genes in Arabidopsis

    OpenAIRE

    Kim, Kyungpil; Jiang, Keni; Teng, Siew Leng; Feldman, Lewis J.; Huang, Haiyan

    2012-01-01

    Motivation: Pathway genes are considered as a group of genes that work cooperatively in the same pathway constituting a fundamental functional grouping in a biological process. Identifying pathway genes has been one of the major tasks in understanding biological processes. However, due to the difficulty in characterizing/inferring different types of biological gene relationships, as well as several computational issues arising from dealing with high-dimensional biological data, deducing ge...

  8. 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

  9. Genetic localization and in vivo characterization of a Monascus azaphilone pigment biosynthetic gene cluster.

    Science.gov (United States)

    Balakrishnan, Bijinu; Karki, Suman; Chiu, Shih-Hau; Kim, Hyun-Ju; Suh, Jae-Won; Nam, Bora; Yoon, Yeo-Min; Chen, Chien-Chi; Kwon, Hyung-Jin

    2013-07-01

    Monascus spp. produce several well-known polyketides such as monacolin K, citrinin, and azaphilone pigments. In this study, the azaphilone pigment biosynthetic gene cluster was identified through T-DNA random mutagenesis in Monascus purpureus. The albino mutant W13 bears a T-DNA insertion upstream of a transcriptional regulator gene (mppR1). The transcription of mppR1 and the nearby polyketide synthase gene (MpPKS5) was significantly repressed in the W13 mutant. Targeted inactivation of MpPKS5 also gave rise to an albino mutant, confirming that mppR1 and MpPKS5 belong to an azaphilone pigment biosynthetic gene cluster. This M. purpureus sequence was used to identify the whole biosynthetic gene cluster in the Monascus pilosus genome. MpPKS5 contains SAT/KS/AT/PT/ACP/MT/R domains, and this domain organization is preserved in other azaphilone polyketide synthases. This biosynthetic gene cluster also encodes fatty acid synthase (FAS), which is predicted to assist the synthesis of 3-oxooactanoyl-CoA and 3-oxodecanoyl-CoA. These 3-oxoacyl compounds are proposed to be incorporated into the azaphilone backbone to complete the pigment biosynthesis. A monooxygenase gene (an azaH and tropB homolog) that is located far downstream of the FAS gene is proposed to be involved in pyrone ring formation. A homology search on other fungal genome sequences suggests that this azaphilone pigment gene cluster also exists in the Penicillium marneffei and Talaromyces stipitatus genomes.

  10. Organization, expression and evolution of a disease resistance gene cluster in soybean.

    Science.gov (United States)

    Graham, Michelle A; Marek, Laura Fredrick; Shoemaker, Randy C

    2002-01-01

    PCR amplification was previously used to identify a cluster of resistance gene analogues (RGAs) on soybean linkage group J. Resistance to powdery mildew (Rmd-c), Phytophthora stem and root rot (Rps2), and an ineffective nodulation gene (Rj2) map within this cluster. BAC fingerprinting and RGA-specific primers were used to develop a contig of BAC clones spanning this region in cultivar "Williams 82" [rps2, Rmd (adult onset), rj2]. Two cDNAs with homology to the TIR/NBD/LRR family of R-genes have also been mapped to opposite ends of a BAC in the contig Gm_Isb001_091F11 (BAC 91F11). Sequence analyses of BAC 91F11 identified 16 different resistance-like gene (RLG) sequences with homology to the TIR/NBD/LRR family of disease resistance genes. Four of these RLGs represent two potentially novel classes of disease resistance genes: TIR/NBD domains fused inframe to a putative defense-related protein (NtPRp27-like) and TIR domains fused inframe to soybean calmodulin Ca(2+)-binding domains. RT-PCR analyses using gene-specific primers allowed us to monitor the expression of individual genes in different tissues and developmental stages. Three genes appeared to be constitutively expressed, while three were differentially expressed. Analyses of the R-genes within this BAC suggest that R-gene evolution in soybean is a complex and dynamic process. PMID:12524363

  11. The Biosynthetic Gene Cluster for Andrastin A in Penicillium roqueforti

    Directory of Open Access Journals (Sweden)

    Juan F. Rojas-Aedo

    2017-05-01

    Full Text Available Penicillium roqueforti is a filamentous fungus involved in the ripening of several kinds of blue cheeses. In addition, this fungus produces several secondary metabolites, including the meroterpenoid compound andrastin A, a promising antitumoral compound. However, to date the genomic cluster responsible for the biosynthesis of this compound in P. roqueforti has not been described. In this work, we have sequenced and annotated a genomic region of approximately 29.4 kbp (named the adr gene cluster that is involved in the biosynthesis of andrastin A in P. roqueforti. This region contains ten genes, named adrA, adrC, adrD, adrE, adrF, adrG, adrH, adrI, adrJ and adrK. Interestingly, the adrB gene previously found in the adr cluster from P. chrysogenum, was found as a residual pseudogene in the adr cluster from P. roqueforti. RNA-mediated gene silencing of each of the ten genes resulted in significant reductions in andrastin A production, confirming that all of them are involved in the biosynthesis of this compound. Of particular interest was the adrC gene, encoding for a major facilitator superfamily transporter. According to our results, this gene is required for the production of andrastin A but does not have any role in its secretion to the extracellular medium. The identification of the adr cluster in P. roqueforti will be important to understand the molecular basis of the production of andrastin A, and for the obtainment of strains of P. roqueforti overproducing andrastin A that might be of interest for the cheese industry.

  12. Design-based re-engineering of biosynthetic gene clusters : plug-and-play in practice

    NARCIS (Netherlands)

    Frasch, Hans-Jörg; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gago, Federico; Parayil, Ajikumar

    2013-01-01

    Synthetic biology is revolutionizing the way in which the biosphere is explored for natural products. Through computational genome mining, thousands of biosynthetic gene clusters are being identified in microbial genomes, which constitute a rich source of potential novel pharmaceuticals. New methods

  13. Design-based re-engineering of biosynthetic gene clusters : plug-and-play in practice

    NARCIS (Netherlands)

    Frasch, Hans-Jörg; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gago, Federico; Parayil, Ajikumar

    2013-01-01

    Synthetic biology is revolutionizing the way in which the biosphere is explored for natural products. Through computational genome mining, thousands of biosynthetic gene clusters are being identified in microbial genomes, which constitute a rich source of potential novel pharmaceuticals. New methods

  14. A predictive approach to identify genes differentially expressed

    Science.gov (United States)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Luís A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

  15. Shared gene structures and clusters of mutually exclusive spliced exons within the metazoan muscle myosin heavy chain genes.

    Directory of Open Access Journals (Sweden)

    Martin Kollmar

    Full Text Available Multicellular animals possess two to three different types of muscle tissues. Striated muscles have considerable ultrastructural similarity and contain a core set of proteins including the muscle myosin heavy chain (Mhc protein. The ATPase activity of this myosin motor protein largely dictates muscle performance at the molecular level. Two different solutions to adjusting myosin properties to different muscle subtypes have been identified so far: Vertebrates and nematodes contain many independent differentially expressed Mhc genes while arthropods have single Mhc genes with clusters of mutually exclusive spliced exons (MXEs. The availability of hundreds of metazoan genomes now allowed us to study whether the ancient bilateria already contained MXEs, how MXE complexity subsequently evolved, and whether additional scenarios to control contractile properties in different muscles could be proposed, By reconstructing the Mhc genes from 116 metazoans we showed that all intron positions within the motor domain coding regions are conserved in all bilateria analysed. The last common ancestor of the bilateria already contained a cluster of MXEs coding for part of the loop-2 actin-binding sequence. Subsequently the protostomes and later the arthropods gained many further clusters while MXEs got completely lost independently in several branches (vertebrates and nematodes and species (for example the annelid Helobdella robusta and the salmon louse Lepeophtheirus salmonis. Several bilateria have been found to encode multiple Mhc genes that might all or in part contain clusters of MXEs. Notable examples are a cluster of six tandemly arrayed Mhc genes, of which two contain MXEs, in the owl limpet Lottia gigantea and four Mhc genes with three encoding MXEs in the predatory mite Metaseiulus occidentalis. Our analysis showed that similar solutions to provide different myosin isoforms (multiple genes or clusters of MXEs or both have independently been developed

  16. 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

    of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental...... 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...

  17. Identifying cancer genes from cancer mutation profiles by cancer functions

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    It is of great importance to identify new cancer genes from the data of large scale genome screenings of gene mutations in cancers. Considering the alternations of some essential functions are indispensable for oncogenesis, we define them as cancer functions and select, as their approximations, a group of detailed functions in GO (Gene Ontology) highly enriched with known cancer genes. To evaluate the efficiency of using cancer functions as features to identify cancer genes, we define, in the screened genes, the known protein kinase cancer genes as gold standard positives and the other kinase genes as gold standard negatives. The results show that cancer associated functions are more efficient in identifying cancer genes than the selection pressure feature. Furthermore, combining cancer functions with the number of non-silent mutations can generate more reliable positive predictions. Finally, with precision 0.42, we suggest a list of 46 kinase genes as candidate cancer genes which are annotated to cancer functions and carry at least 3 non-silent mutations.

  18. Identification of transcriptional activators for thienamycin and cephamycin C biosynthetic genes within the thienamycin gene cluster from Streptomyces cattleya.

    Science.gov (United States)

    Rodríguez, Miriam; Núñez, Luz Elena; Braña, Alfredo F; Méndez, Carmen; Salas, José A; Blanco, Gloria

    2008-08-01

    Two regulatory genes, thnI and thnU, were identified in the thienamycin (thn) gene cluster from Streptomyces cattleya. ThnI resembles LysR-type transcriptional activators and ThnU belongs to the SARP family of transcriptional activators. Their functional role was established after independent inactivation by gene replacement together with transcriptional analysis involving reverse transcription polymerase chain reaction (RT-PCR). Deletion of thnI abolished thienamycin production showing its involvement in thienamycin biosynthesis. Gene expression analysis applied to the thn gene cluster demonstrated that ThnI is a transcriptional activator essential for thienamycin biosynthesis that regulates the expression of nine genes involved in thienamycin assembly and export (thnH, thnJ, thnK, thnL, thnM, thnN, thnO, thnP and thnQ). Unexpectedly, the thnU disrupted mutant was not affected in thienamycin production but turned out to be essential for cephamycin C biosynthesis. Transcript analysis applied to early and late structural genes for cephamycin C biosynthesis (pcbAB and cmcI), revealed that ThnU is the transcriptional activator of these cephamycin C genes although they are not physically linked to the thn cluster. In addition, it was shown that deletion of thnI has an upregulatory effect on pcbAB and cmcI transcription consistent with a significant increase in cephamycin C biosynthesis in this mutant.

  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. Organization and Differential Regulation of a Cluster of Lignin Peroxidase Genes of Phanerochaete chrysosporium

    Science.gov (United States)

    Stewart, Philip; Cullen, Daniel

    1999-01-01

    The lignin peroxidases of Phanerochaete chrysosporium are encoded by a minimum of 10 closely related genes. Physical and genetic mapping of a cluster of eight lip genes revealed six genes occurring in pairs and transcriptionally convergent, suggesting that portions of the lip family arose by gene duplication events. The completed sequence of lipG and lipJ, together with previously published sequences, allowed phylogenetic and intron/exon classifications, indicating two main branches within the lip family. Competitive reverse transcription-PCR was used to assess lip transcript levels in both carbon- and nitrogen-limited media. Transcript patterns showed differential regulation of lip genes in response to medium composition. No apparent correlation was observed between genomic organization and transcript levels. Both constitutive and upregulated transcripts, structurally unrelated to peroxidases, were identified within the lip cluster. PMID:10348854

  1. Genome mining demonstrates the widespread occurrence of gene clusters encoding bacteriocins in cyanobacteria.

    Science.gov (United States)

    Wang, Hao; Fewer, David P; Sivonen, Kaarina

    2011-01-01

    Cyanobacteria are a rich source of natural products with interesting biological activities. Many of these are peptides and the end products of a non-ribosomal pathway. However, several cyanobacterial peptide classes were recently shown to be produced through the proteolytic cleavage and post-translational modification of short precursor peptides. A new class of bacteriocins produced through the proteolytic cleavage and heterocyclization of precursor proteins was recently identified from marine cyanobacteria. Here we show the widespread occurrence of bacteriocin gene clusters in cyanobacteria through comparative analysis of 58 cyanobacterial genomes. A total of 145 bacteriocin gene clusters were discovered through genome mining. These clusters encoded 290 putative bacteriocin precursors. They ranged in length from 28 to 164 amino acids with very little sequence conservation of the core peptide. The gene clusters could be classified into seven groups according to their gene organization and domain composition. This classification is supported by phylogenetic analysis, which further indicated independent evolutionary trajectories of gene clusters in different groups. Our data suggests that cyanobacteria are a prolific source of low-molecular weight post-translationally modified peptides.

  2. Genome mining demonstrates the widespread occurrence of gene clusters encoding bacteriocins in cyanobacteria.

    Directory of Open Access Journals (Sweden)

    Hao Wang

    Full Text Available Cyanobacteria are a rich source of natural products with interesting biological activities. Many of these are peptides and the end products of a non-ribosomal pathway. However, several cyanobacterial peptide classes were recently shown to be produced through the proteolytic cleavage and post-translational modification of short precursor peptides. A new class of bacteriocins produced through the proteolytic cleavage and heterocyclization of precursor proteins was recently identified from marine cyanobacteria. Here we show the widespread occurrence of bacteriocin gene clusters in cyanobacteria through comparative analysis of 58 cyanobacterial genomes. A total of 145 bacteriocin gene clusters were discovered through genome mining. These clusters encoded 290 putative bacteriocin precursors. They ranged in length from 28 to 164 amino acids with very little sequence conservation of the core peptide. The gene clusters could be classified into seven groups according to their gene organization and domain composition. This classification is supported by phylogenetic analysis, which further indicated independent evolutionary trajectories of gene clusters in different groups. Our data suggests that cyanobacteria are a prolific source of low-molecular weight post-translationally modified peptides.

  3. DNACLUST: accurate and efficient clustering of phylogenetic marker genes

    Directory of Open Access Journals (Sweden)

    Liu Bo

    2011-06-01

    Full Text Available Abstract Background Clustering is a fundamental operation in the analysis of biological sequence data. New DNA sequencing technologies have dramatically increased the rate at which we can generate data, resulting in datasets that cannot be efficiently analyzed by traditional clustering methods. This is particularly true in the context of taxonomic profiling of microbial communities through direct sequencing of phylogenetic markers (e.g. 16S rRNA - the domain that motivated the work described in this paper. Many analysis approaches rely on an initial clustering step aimed at identifying sequences that belong to the same operational taxonomic unit (OTU. When defining OTUs (which have no universally accepted definition, scientists must balance a trade-off between computational efficiency and biological accuracy, as accurately estimating an environment's phylogenetic composition requires computationally-intensive analyses. We propose that efficient and mathematically well defined clustering methods can benefit existing taxonomic profiling approaches in two ways: (i the resulting clusters can be substituted for OTUs in certain applications; and (ii the clustering effectively reduces the size of the data-sets that need to be analyzed by complex phylogenetic pipelines (e.g., only one sequence per cluster needs to be provided to downstream analyses. Results To address the challenges outlined above, we developed DNACLUST, a fast clustering tool specifically designed for clustering highly-similar DNA sequences. Given a set of sequences and a sequence similarity threshold, DNACLUST creates clusters whose radius is guaranteed not to exceed the specified threshold. Underlying DNACLUST is a greedy clustering strategy that owes its performance to novel sequence alignment and k-mer based filtering algorithms. DNACLUST can also produce multiple sequence alignments for every cluster, allowing users to manually inspect clustering results, and enabling more

  4. An Sp185/333 gene cluster from the purple sea urchin and putative microsatellite-mediated gene diversification

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    Buckley Katherine M

    2010-10-01

    Full Text Available Abstract Background The immune system of the purple sea urchin, Strongylocentrotus purpuratus, is complex and sophisticated. An important component of sea urchin immunity is the Sp185/333 gene family, which is significantly upregulated in immunologically challenged animals. The Sp185/333 genes are less than 2 kb with two exons and are members of a large diverse family composed of greater than 40 genes. The S. purpuratus genome assembly, however, contains only six Sp185/333 genes. This underrepresentation could be due to the difficulties that large gene families present in shotgun assembly, where multiple similar genes can be collapsed into a single consensus gene. Results To understand the genomic organization of the Sp185/333 gene family, a BAC insert containing Sp185/333 genes was assembled, with careful attention to avoiding artifacts resulting from collapse or artificial duplication/expansion of very similar genes. Twelve candidate BAC assemblies were generated with varying parameters and the optimal assembly was identified by PCR, restriction digests, and subclone sequencing. The validated assembly contained six Sp185/333 genes that were clustered in a 34 kb region at one end of the BAC with five of the six genes tightly clustered within 20 kb. The Sp185/333 genes in this cluster were no more similar to each other than to previously sequenced Sp185/333 genes isolated from three different animals. This was unexpected given their proximity and putative effects of gene homogenization in closely linked, similar genes. All six genes displayed significant similarity including both 5' and 3' flanking regions, which were bounded by microsatellites. Three of the Sp185/333 genes and their flanking regions were tandemly duplicated such that each repeated segment consisted of a gene plus 0.7 kb 5' and 2.4 kb 3' of the gene (4.5 kb total. Both edges of the segmental duplications were bounded by different microsatellites. Conclusions The high sequence

  5. Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

    Science.gov (United States)

    Wolen, Aaron R; Miles, Michael F

    2012-01-01

    For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

  6. 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.

  7. Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

    Science.gov (United States)

    Yang, Xiaowen; Li, Yajie; Zang, Juan; Li, Yexia; Bie, Pengfei; Lu, Yanli; Wu, Qingmin

    2016-04-01

    Brucella spp. are facultative intracellular pathogens, that cause a contagious zoonotic disease, that can result in such outcomes as abortion or sterility in susceptible animal hosts and grave, debilitating illness in humans. For deciphering the survival mechanism of Brucella spp. in vivo, 42 Brucella complete genomes from NCBI were analyzed for the pan-genome and core genome by identification of their composition and function of Brucella genomes. The results showed that the total 132,143 protein-coding genes in these genomes were divided into 5369 clusters. Among these, 1710 clusters were associated with the core genome, 1182 clusters with strain-specific genes and 2477 clusters with dispensable genomes. COG analysis indicated that 44 % of the core genes were devoted to metabolism, which were mainly responsible for energy production and conversion (COG category C), and amino acid transport and metabolism (COG category E). Meanwhile, approximately 35 % of the core genes were in positive selection. In addition, 1252 potential essential genes were predicted in the core genome by comparison with a prokaryote database of essential genes. The results suggested that the core genes in Brucella genomes are relatively conservation, and the energy and amino acid metabolism play a more important role in the process of growth and reproduction in Brucella spp. This study might help us to better understand the mechanisms of Brucella persistent infection and provide some clues for further exploring the gene modules of the intracellular survival in Brucella spp.

  8. Apple contains receptor-like genes homologous to the Cladosporium fulvum resistance gene family of tomato with a cluster of genes cosegregating with Vf apple scab resistance.

    Science.gov (United States)

    Vinatzer, B A; Patocchi, A; Gianfranceschi, L; Tartarini, S; Zhang, H B; Gessler, C; Sansavini, S

    2001-04-01

    Scab caused by the fungal pathogen Venturia inaequalis is the most common disease of cultivated apple (Malus x domestica Borkh.). Monogenic resistance against scab is found in some small-fruited wild Malus species and has been used in apple breeding for scab resistance. Vf resistance of Malus floribunda 821 is the most widely used scab resistance source. Because breeding a high-quality cultivar in perennial fruit trees takes dozens of years, cloning disease resistance genes and using them in the transformation of high-quality apple varieties would be advantageous. We report the identification of a cluster of receptor-like genes with homology to the Cladosporium fulvum (Cf) resistance gene family of tomato on bacterial artificial chromosome clones derived from the Vf scab resistance locus. Three members of the cluster were sequenced completely. Similar to the Cf gene family of tomato, the deduced amino acid sequences coded by these genes contain an extracellular leucine-rich repeat domain and a transmembrane domain. The transcription of three members of the cluster was determined by reverse transcriptionpolymerase chain reaction to be constitutive, and the transcription and translation start of one member was verified by 5' rapid amplification of cDNA ends. We discuss the parallels between Cf resistance of tomato and Vf resistance of apple and the possibility that one of the members of the gene cluster is the Vf gene. Cf homologs from other regions of the apple genome also were identified and are likely to present other scab resistance genes.

  9. Characterisation of the paralytic shellfish toxin biosynthesis gene clusters in Anabaena circinalis AWQC131C and Aphanizomenon sp. NH-5

    Directory of Open Access Journals (Sweden)

    Neilan Brett A

    2009-03-01

    Full Text Available Abstract Background Saxitoxin and its analogues collectively known as the paralytic shellfish toxins (PSTs are neurotoxic alkaloids and are the cause of the syndrome named paralytic shellfish poisoning. PSTs are produced by a unique biosynthetic pathway, which involves reactions that are rare in microbial metabolic pathways. Nevertheless, distantly related organisms such as dinoflagellates and cyanobacteria appear to produce these toxins using the same pathway. Hypothesised explanations for such an unusual phylogenetic distribution of this shared uncommon metabolic pathway, include a polyphyletic origin, an involvement of symbiotic bacteria, and horizontal gene transfer. Results We describe the identification, annotation and bioinformatic characterisation of the putative paralytic shellfish toxin biosynthesis clusters in an Australian isolate of Anabaena circinalis and an American isolate of Aphanizomenon sp., both members of the Nostocales. These putative PST gene clusters span approximately 28 kb and contain genes coding for the biosynthesis and export of the toxin. A putative insertion/excision site in the Australian Anabaena circinalis AWQC131C was identified, and the organization and evolution of the gene clusters are discussed. A biosynthetic pathway leading to the formation of saxitoxin and its analogues in these organisms is proposed. Conclusion The PST biosynthesis gene cluster presents a mosaic structure, whereby genes have apparently transposed in segments of varying size, resulting in different gene arrangements in all three sxt clusters sequenced so far. The gene cluster organizational structure and sequence similarity seems to reflect the phylogeny of the producer organisms, indicating that the gene clusters have an ancient origin, or that their lateral transfer was also an ancient event. The knowledge we gain from the characterisation of the PST biosynthesis gene clusters, including the identity and sequence of the genes involved

  10. 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.

  11. Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes

    NARCIS (Netherlands)

    J. Molenaar (Jan); J. Koster (Jan); D. Zwijnenburg (Danny); P. van Sluis (Peter); L.J. Valentijn (Linda); I. van der Ploeg (Ida); M. Hamdi (Mohamed); J. van Nes (Johan); B.A. Westerman (Bart); J. van Arkel (Jennemiek); M.E. Ebus; F. Haneveld (Franciska); A. Lakeman (Arjan); L. Schild (Linda); P. Molenaar (Piet); P. Stroeken (Peter); M.M. van Noesel (Max); I. Øra (Ingrid); J.P. di Santo (James); H.N. Caron (Huib); E.M. Westerhout (Ellen); R. Versteeg (Rogier)

    2012-01-01

    textabstractNeuroblastoma is a childhood tumour of the peripheral sympathetic nervous system. The pathogenesis has for a long time been quite enigmatic, as only very few gene defects were identified in this often lethal tumour. Frequently detected gene alterations are limited to MYCN amplification (

  12. Identifying patterns in treatment response profiles in acute bipolar mania: a cluster analysis approach

    Directory of Open Access Journals (Sweden)

    Houston John P

    2008-07-01

    Full Text Available Abstract Background Patients with acute mania respond differentially to treatment and, in many cases, fail to obtain or sustain symptom remission. The objective of this exploratory analysis was to characterize response in bipolar disorder by identifying groups of patients with similar manic symptom response profiles. Methods Patients (n = 222 were selected from a randomized, double-blind study of treatment with olanzapine or divalproex in bipolar I disorder, manic or mixed episode, with or without psychotic features. Hierarchical clustering based on Ward's distance was used to identify groups of patients based on Young-Mania Rating Scale (YMRS total scores at each of 5 assessments over 7 weeks. Logistic regression was used to identify baseline predictors for clusters of interest. Results Four distinct clusters of patients were identified: Cluster 1 (n = 64: patients did not maintain a response (YMRS total scores ≤ 12; Cluster 2 (n = 92: patients responded rapidly (within less than a week and response was maintained; Cluster 3 (n = 36: patients responded rapidly but relapsed soon afterwards (YMRS ≥ 15; Cluster 4 (n = 30: patients responded slowly (≥ 2 weeks and response was maintained. Predictive models using baseline variables found YMRS Item 10 (Appearance, and psychosis to be significant predictors for Clusters 1 and 4 vs. Clusters 2 and 3, but none of the baseline characteristics allowed discriminating between Clusters 1 vs. 4. Experiencing a mixed episode at baseline predicted membership in Clusters 2 and 3 vs. Clusters 1 and 4. Treatment with divalproex, larger number of previous manic episodes, lack of disruptive-aggressive behavior, and more prominent depressive symptoms at baseline were predictors for Cluster 3 vs. 2. Conclusion Distinct treatment response profiles can be predicted by clinical features at baseline. The presence of these features as potential risk factors for relapse in patients who have responded to treatment

  13. Proteomic Analysis Identifies Outcome-Predictive Clusters in Patients with Peripheral T-Cell Lymphoma, Not otherwise specified

    DEFF Research Database (Denmark)

    Ludvigsen, Maja; Pedersen, Martin Bjerregård; Poulsen, T.S.

    2014-01-01

    Proteomic Analysis Identifies Outcome-Predictive Clusters in Patients with Peripheral T-Cell Lymphoma, Not otherwise specified......Proteomic Analysis Identifies Outcome-Predictive Clusters in Patients with Peripheral T-Cell Lymphoma, Not otherwise specified...

  14. Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

    Science.gov (United States)

    Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.

    2010-06-01

    Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance

  15. A Gene Selection Approach based on Clustering for Classification Tasks in Colon Cancer

    Directory of Open Access Journals (Sweden)

    José Antonio CASTELLANOS GARZÓN

    2016-06-01

    Full Text Available Gene selection (GS is an important research area in the analysis of DNA-microarray data, since it involves gene discovery meaningful for a particular target annotation or able to discriminate expression profiles of samples coming from different populations. In this context, a wide number of filter methods have been proposed in the literature to identify subsets of relevant genes in accordance with prefixed targets. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem (GS remains a challenge. Hence, this paper proposes a novel approach for gene selection by using cluster techniques and filter methods on the found groupings to achieve informative gene subsets. As a result of applying our methodology to Colon cancer data, we have identified the best informative gene subset between several one subsets. According to the above, the reached results have proven the reliability of the approach given in this paper.

  16. Measures of Galaxy Environment - III. Difficulties in identifying proto-clusters at z ~ 2

    CERN Document Server

    Shattow, Genevieve M; Skibba, Ramin A; Muldrew, Stuart I; Pearce, Frazer R; Abbas, Ummi

    2013-01-01

    Galaxy environment is frequently discussed, but inconsistently defined. It is especially difficult to measure at high redshift where only photometric redshifts are available. With a focus on early forming proto-clusters, we use a semi-analytical model of galaxy formation to show how the environment measurement around high redshift galaxies is sensitive to both scale and metric, as well as to cluster viewing angle, evolutionary state, and the availability of either spectroscopic or photometric data. We use two types of environment metrics (nearest neighbour and fixed aperture) at a range of scales on simulated high-z clusters to see how "observed" overdensities compare to "real" overdensities. We also "observationally" identify z = 2 proto-cluster candidates in our model and track the growth histories of their parent halos through time, considering in particular their final state at z = 0. Although the measured environment of early forming clusters is critically dependent on all of the above effects (and in pa...

  17. Multi-class clustering of cancer subtypes through SVM based ensemble of pareto-optimal solutions for gene marker identification.

    Directory of Open Access Journals (Sweden)

    Anirban Mukhopadhyay

    Full Text Available With the advancement of microarray technology, it is now possible to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer subtype, which helps in successful diagnosis of particular cancer types. In this article, we have presented an unsupervised cancer classification technique based on multiobjective genetic clustering of the tissue samples. In this regard, a real-coded encoding of the cluster centers is used and cluster compactness and separation are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of non-dominated solutions. A novel approach to combine the clustering information possessed by the non-dominated solutions through Support Vector Machine (SVM classifier has been proposed. Final clustering is obtained by consensus among the clusterings yielded by different kernel functions. The performance of the proposed multiobjective clustering method has been compared with that of several other microarray clustering algorithms for three publicly available benchmark cancer datasets. Moreover, statistical significance tests have been conducted to establish the statistical superiority of the proposed clustering method. Furthermore, relevant gene markers have been identified using the clustering result produced by the proposed clustering method and demonstrated visually. Biological relationships among the gene markers are also studied based on gene ontology. The results obtained are found to be promising and can possibly have important impact in the area of unsupervised cancer classification as well as gene marker identification for multiple cancer subtypes.

  18. Rice Transcriptome Analysis to Identify Possible Herbicide Quinclorac Detoxification Genes

    Directory of Open Access Journals (Sweden)

    Wenying eXu

    2015-09-01

    Full Text Available Quinclorac is a highly selective auxin-type herbicide, and is widely used in the effective control of barnyard grass in paddy rice fields, improving the world’s rice yield. The herbicide mode of action of quinclorac has been proposed and hormone interactions affect quinclorac signaling. Because of widespread use, quinclorac may be transported outside rice fields with the drainage waters, leading to soil and water pollution and environmental health problems.In this study, we used 57K Affymetrix rice whole-genome array to identify quinclorac signaling response genes to study the molecular mechanisms of action and detoxification of quinclorac in rice plants. Overall, 637 probe sets were identified with differential expression levels under either 6 or 24 h of quinclorac treatment. Auxin-related genes such as GH3 and OsIAAs responded to quinclorac treatment. Gene Ontology analysis showed that genes of detoxification-related family genes were significantly enriched, including cytochrome P450, GST, UGT, and ABC and drug transporter genes. Moreover, real-time RT-PCR analysis showed that top candidate P450 families such as CYP81, CYP709C and CYP72A genes were universally induced by different herbicides. Some Arabidopsis genes for the same P450 family were up-regulated under quinclorac treatment.We conduct rice whole-genome GeneChip analysis and the first global identification of quinclorac response genes. This work may provide potential markers for detoxification of quinclorac and biomonitors of environmental chemical pollution.

  19. Identifying Gene Regulatory Networks in Arabidopsis by In Silico Prediction, Yeast-1-Hybrid, and Inducible Gene Profiling Assays.

    Science.gov (United States)

    Sparks, Erin E; Benfey, Philip N

    2016-01-01

    A system-wide understanding of gene regulation will provide deep insights into plant development and physiology. In this chapter we describe a threefold approach to identify the gene regulatory networks in Arabidopsis thaliana that function in a specific tissue or biological process. Since no single method is sufficient to establish comprehensive and high-confidence gene regulatory networks, we focus on the integration of three approaches. First, we describe an in silico prediction method of transcription factor-DNA binding, then an in vivo assay of transcription factor-DNA binding by yeast-1-hybrid and lastly the identification of co-expression clusters by transcription factor induction in planta. Each of these methods provides a unique tool to advance our understanding of gene regulation, and together provide a robust model for the generation of gene regulatory networks.

  20. Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

    Directory of Open Access Journals (Sweden)

    Wolfinger Russell D

    2007-02-01

    buff denoting samples having pain type representative of angina and non-angina respectively with an accuracy of 79%. This is on par with, or better than, the assignment accuracy of the heart disease samples by several well-known and successful clustering algorithms. Following modk-prototypes clustering of the acetaminophen-exposed samples, informative genes from the cluster prototypes were identified that are descriptive of, and phenotypically anchored to, levels of necrosis of the centrilobular region of the rat liver. The biological processes cell growth and/or maintenance, amine metabolism, and stress response were shown to discern between no and moderate levels of acetaminophen-induced centrilobular necrosis. The use of well-known and traditional measurements directly in the clustering provides some guarantee that the resulting clusters will be meaningfully interpretable.

  1. 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...

  2. Identifying glioblastoma gene networks based on hypergeometric test analysis.

    Directory of Open Access Journals (Sweden)

    Vasileios Stathias

    Full Text Available Patient specific therapy is emerging as an important possibility for many cancer patients. However, to identify such therapies it is essential to determine the genomic and transcriptional alterations present in one tumor relative to control samples. This presents a challenge since use of a single sample precludes many standard statistical analysis techniques. We reasoned that one means of addressing this issue is by comparing transcriptional changes in one tumor with those observed in a large cohort of patients analyzed by The Cancer Genome Atlas (TCGA. To test this directly, we devised a bioinformatics pipeline to identify differentially expressed genes in tumors resected from patients suffering from the most common malignant adult brain tumor, glioblastoma (GBM. We performed RNA sequencing on tumors from individual GBM patients and filtered the results through the TCGA database in order to identify possible gene networks that are overrepresented in GBM samples relative to controls. Importantly, we demonstrate that hypergeometric-based analysis of gene pairs identifies gene networks that validate experimentally. These studies identify a putative workflow for uncovering differentially expressed patient specific genes and gene networks for GBM and other cancers.

  3. Visualization of mappings between the gene ontology and cluster trees

    Science.gov (United States)

    Jusufi, Ilir; Kerren, Andreas; Aleksakhin, Vladyslav; Schreiber, Falk

    2012-01-01

    Ontologies and hierarchical clustering are both important tools in biology and medicine to study high-throughput data such as transcriptomics and metabolomics data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze and visualize data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set, but are usually considered independently. However, often a combined view is desired: visualizing a large data set in the context of an ontology under consideration of a clustering of the data. This paper proposes a new visualization method for this task.

  4. Transcription mediated insulation and interference direct gene cluster expression switches.

    Science.gov (United States)

    Nguyen, Tania; Fischl, Harry; Howe, Françoise S; Woloszczuk, Ronja; Serra Barros, Ana; Xu, Zhenyu; Brown, David; Murray, Struan C; Haenni, Simon; Halstead, James M; O'Connor, Leigh; Shipkovenska, Gergana; Steinmetz, Lars M; Mellor, Jane

    2014-11-19

    In yeast, many tandemly arranged genes show peak expression in different phases of the metabolic cycle (YMC) or in different carbon sources, indicative of regulation by a bi-modal switch, but it is not clear how these switches are controlled. Using native elongating transcript analysis (NET-seq), we show that transcription itself is a component of bi-modal switches, facilitating reciprocal expression in gene clusters. HMS2, encoding a growth-regulated transcription factor, switches between sense- or antisense-dominant states that also coordinate up- and down-regulation of transcription at neighbouring genes. Engineering HMS2 reveals alternative mono-, di- or tri-cistronic and antisense transcription units (TUs), using different promoter and terminator combinations, that underlie state-switching. Promoters or terminators are excluded from functional TUs by read-through transcriptional interference, while antisense TUs insulate downstream genes from interference. We propose that the balance of transcriptional insulation and interference at gene clusters facilitates gene expression switches during intracellular and extracellular environmental change.

  5. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Directory of Open Access Journals (Sweden)

    Jun-Chao Guo

    Full Text Available The extremely dismal prognosis of pancreatic cancer (PC is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  6. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Science.gov (United States)

    Guo, Jun-Chao; Li, Jian; Yang, Ying-Chi; Zhou, Li; Zhang, Tai-Ping; Zhao, Yu-Pei

    2013-01-01

    The extremely dismal prognosis of pancreatic cancer (PC) is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA)-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes) were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  7. 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.

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

    DEFF Research Database (Denmark)

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

    approach grouping variants accordingly to gene position, thus lowering the number of statistical tests performed and increasing the probability of identifying genes with small to moderate effects. Using this approach we identify numerous genes associated with different types of stresses in Drosophila...

  9. Transcriptome analysis identifies genes involved in ethanol response of Saccharomyces cerevisiae in Agave tequilana juice.

    Science.gov (United States)

    Ramirez-Córdova, Jesús; Drnevich, Jenny; Madrigal-Pulido, Jaime Alberto; Arrizon, Javier; Allen, Kirk; Martínez-Velázquez, Moisés; Alvarez-Maya, Ikuri

    2012-08-01

    During ethanol fermentation, yeast cells are exposed to stress due to the accumulation of ethanol, cell growth is altered and the output of the target product is reduced. For Agave beverages, like tequila, no reports have been published on the global gene expression under ethanol stress. In this work, we used microarray analysis to identify Saccharomyces cerevisiae genes involved in the ethanol response. Gene expression of a tequila yeast strain of S. cerevisiae (AR5) was explored by comparing global gene expression with that of laboratory strain S288C, both after ethanol exposure. Additionally, we used two different culture conditions, cells grown in Agave tequilana juice as a natural fermentation media or grown in yeast-extract peptone dextrose as artificial media. Of the 6368 S. cerevisiae genes in the microarray, 657 genes were identified that had different expression responses to ethanol stress due to strain and/or media. A cluster of 28 genes was found over-expressed specifically in the AR5 tequila strain that could be involved in the adaptation to tequila yeast fermentation, 14 of which are unknown such as yor343c, ylr162w, ygr182c, ymr265c, yer053c-a or ydr415c. These could be the most suitable genes for transforming tequila yeast to increase ethanol tolerance in the tequila fermentation process. Other genes involved in response to stress (RFC4, TSA1, MLH1, PAU3, RAD53) or transport (CYB2, TIP20, QCR9) were expressed in the same cluster. Unknown genes could be good candidates for the development of recombinant yeasts with ethanol tolerance for use in industrial tequila fermentation.

  10. Comparing the biological coherence of network clusters identified by different detection algorithms

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Protein-protein interaction networks serve to carry out basic molecular activity in the cell. Detecting the modular structures from the protein-protein interaction network is important for understanding the organization, function and dynamics of a biological system. In order to identify functional neighborhoods based on network topology, many network cluster identification algorithms have been developed. However, each algorithm might dissect a network from a different aspect and may provide different insight on the network partition. In order to objectively evaluate the performance of four commonly used cluster detection algorithms: molecular complex detection (MCODE), NetworkBlast, shortest-distance clustering (SDC) and Girvan-Newman (G-N) algorithm, we compared the biological coherence of the network clusters found by these algorithms through a uniform evaluation framework. Each algorithm was utilized to find network clusters in two different protein-protein interaction networks with various parameters. Comparison of the resulting network clusters indicates that clusters found by MCODE and SDC are of higher biological coherence than those by NetworkBlast and G-N algorithm.

  11. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    Science.gov (United States)

    Vyazunova, Irina; Maklakova, Vilena I; Berman, Samuel; De, Ishani; Steffen, Megan D; Hong, Won; Lincoln, Hayley; Morrissy, A Sorana; Taylor, Michael D; Akagi, Keiko; Brennan, Cameron W; Rodriguez, Fausto J; Collier, Lara S

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.

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

    OpenAIRE

    SPIERING, MARTIN J.; Moon, Christina D.; Wilkinson, Heather H.; Christopher L Schardl

    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 ...

  13. Polymorphisms and linkage analysis for ICAM-1 and the selectin gene cluster

    Energy Technology Data Exchange (ETDEWEB)

    Vora, D.K.; Rosenbloom, C.L.; Cottingham, R.W. [Baylor College of Medicine, Houston, TX (United States)] [and others

    1994-06-01

    Genetic polymorphisms in leukocyte and endothelial cell adhesion molecules may be important variables with regard to susceptibility to multifactorial disease processes that include an inflammatory component. For this reason, polymorphisms were sought for intercellular adhesion molecule-1 (ICAM-1; gene symbol ICAM1) and for the three genes in the selectin cluster, P-selectin, L-selectin, and E-selectin (gene symbols SELP, SELL, and SELE, respectively). Two amino acid polymorphisms were identified for ICAM-1; Gly or Arg at codon 241 and Lys or Glu at codon 469. Dinucleotide repeat polymorphisms were identified in the 3{prime}-untranslated region for ICAM-1 and in intron 9 for P-selectin. Restriction fragment length polymorphisms were found using cDNAs for each of the three selectin genes as probes; E-selectin with BglII, P-selectin with ScaI, and L-selectin with HincII. Linkage analysis was performed for the selectin gene cluster and for ICAM-1 using the CEPH families; ICAM-1 is very tightly linked to the LDL receptor on chromosome 19, and the selectin cluster is linked to markers at chromosome 1q23. 41 refs., 2 tabs.

  14. Tracing evolutionary footprints to identify novel gene functional linkages.

    Directory of Open Access Journals (Sweden)

    Yong Chen

    Full Text Available Systematic determination of gene function is an essential step in fully understanding the precise contribution of each gene for the proper execution of molecular functions in the cell. Gene functional linkage is defined as to describe the relationship of a group of genes with similar functions. With thousands of genomes sequenced, there arises a great opportunity to utilize gene evolutionary information to identify gene functional linkages. To this end, we established a computational method (called TRACE to trace gene footprints through a gene functional network constructed from 341 prokaryotic genomes. TRACE performance was validated and successfully tested to predict enzyme functions as well as components of pathway. A so far undescribed chromosome partitioning-like protein ro03654 of an oleaginous bacteria Rhodococcus sp. RHA1 (RHA1 was predicted and verified experimentally with its deletion mutant showing growth inhibition compared to RHA1 wild type. In addition, four proteins were predicted to act as prokaryotic SNARE-like proteins, and two of them were shown to be localized at the plasma membrane. Thus, we believe that TRACE is an effective new method to infer prokaryotic gene functional linkages by tracing evolutionary events.

  15. Loss of Bloom syndrome protein destabilizes human gene cluster architecture.

    Science.gov (United States)

    Killen, Michael W; Stults, Dawn M; Adachi, Noritaka; Hanakahi, Les; Pierce, Andrew J

    2009-09-15

    Bloom syndrome confers strong predisposition to malignancy in multiple tissue types. The Bloom syndrome patient (BLM) protein defective in the disease biochemically functions as a Holliday junction dissolvase and human cells lacking functional BLM show 10-fold elevated rates of sister chromatid exchange. Collectively, these phenomena suggest that dysregulated mitotic recombination drives the genomic instability underpinning the development of cancer in these individuals. Here we use physical analysis of the highly repeated, highly self-similar human ribosomal RNA gene clusters as sentinel biomarkers for dysregulated homologous recombination to demonstrate that loss of BLM protein function causes a striking increase in spontaneous molecular level genomic restructuring. Analysis of single-cell derived sub-clonal populations from wild-type human cell lines shows that gene cluster architecture is ordinarily very faithfully preserved under mitosis, but is so unstable in cell lines derived from BLMs as to make gene cluster architecture in different sub-clonal populations essentially unrecognizable one from another. Human cells defective in a different RecQ helicase, the WRN protein involved in the premature aging Werner syndrome, do not exhibit the gene cluster instability (GCI) phenotype, indicating that the BLM protein specifically, rather than RecQ helicases generally, holds back this recombination-mediated genomic instability. An ataxia-telangiectasia defective cell line also shows elevated rDNA GCI, although not to the extent of BLM defective cells. Genomic restructuring mediated by dysregulated recombination between the abundant low-copy repeats in the human genome may prove to be an important additional mechanism of genomic instability driving the initiation and progression of human cancer.

  16. Evaluation of clustering algorithms for gene expression data using gene ontology annotations

    Institute of Scientific and Technical Information of China (English)

    MA Ning; ZHANG Zheng-guo

    2012-01-01

    Background Clustering is a useful exploratory technique for interpreting gene expression data to reveal groups of genes sharing common functional attributes.Biologists frequently face the problem of choosing an appropriate algorithm.We aimed to provide a standalone,easily accessible and biologically oriented criterion for expression data clustering evaluation.Methods An external criterion utilizing annotation based similarities between genes is proposed in this work.Gene ontology information is employed as the annotation source.Comparisons among six widely used clustering algorithms over various types of gene expression data sets were carried out based on the criterion proposed.Results The rank of these algorithms given by the criterion coincides with our common knowledge.Single-linkage has significantly poorer performance,even worse than the random algorithm.Ward's method archives the best performance in most cases.Conclusions The criterion proposed has a strong ability to distinguish among different clustering algorithms with different distance measurements.It is also demonstrated that analyzing main contributors of the criterion may offer some guidelines in finding local compact clusters.As an addition,we suggest using Ward's algorithm for gene expression data analysis.

  17. Genome-wide upstream motif analysis of Cryptosporidium parvum genes clustered by expression profile.

    Science.gov (United States)

    Oberstaller, Jenna; Joseph, Sandeep J; Kissinger, Jessica C

    2013-07-29

    There are very few molecular genetic tools available to study the apicomplexan parasite Cryptosporidium parvum. The organism is not amenable to continuous in vitro cultivation or transfection, and purification of intracellular developmental stages in sufficient numbers for most downstream molecular applications is difficult and expensive since animal hosts are required. As such, very little is known about gene regulation in C. parvum. We have clustered whole-genome gene expression profiles generated from a previous study of seven post-infection time points of 3,281 genes to identify genes that show similar expression patterns throughout the first 72 hours of in vitro epithelial cell culture. We used the algorithms MEME, AlignACE and FIRE to identify conserved, overrepresented DNA motifs in the upstream promoter region of genes with similar expression profiles. The most overrepresented motifs were E2F (5'-TGGCGCCA-3'); G-box (5'-G.GGGG-3'); a well-documented ApiAP2 binding motif (5'-TGCAT-3'), and an unknown motif (5'-[A/C] AACTA-3'). We generated a recombinant C. parvum DNA-binding protein domain from a putative ApiAP2 transcription factor [CryptoDB: cgd8_810] and determined its binding specificity using protein-binding microarrays. We demonstrate that cgd8_810 can putatively bind the overrepresented G-box motif, implicating this ApiAP2 in the regulation of many gene clusters. Several DNA motifs were identified in the upstream sequences of gene clusters that might serve as potential cis-regulatory elements. These motifs, in concert with protein DNA binding site data, establish for the first time the beginnings of a global C. parvum gene regulatory map that will contribute to our understanding of the development of this zoonotic parasite.

  18. Distinct Phenotypes of Cigarette Smokers Identified by Cluster Analysis of Patients with Severe Asthma.

    Science.gov (United States)

    Konno, Satoshi; Taniguchi, Natsuko; Makita, Hironi; Nakamaru, Yuji; Shimizu, Kaoruko; Shijubo, Noriharu; Fuke, Satoshi; Takeyabu, Kimihiro; Oguri, Mitsuru; Kimura, Hirokazu; Maeda, Yukiko; Suzuki, Masaru; Nagai, Katsura; Ito, Yoichi M; Wenzel, Sally E; Nishimura, Masaharu

    2015-12-01

    Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asthma. Cluster analysis has been applied to explore novel phenotypes, which are not based on any a priori hypotheses. To explore novel severe asthma phenotypes by cluster analysis when including cigarette smokers. We recruited a total of 127 subjects with severe asthma, including 59 current or ex-smokers, from our university hospital and its 29 affiliated hospitals/pulmonary clinics. Twelve clinical variables obtained during a 2-day hospital stay were used for cluster analysis. After clustering using clinical variables, the sputum levels of 14 molecules were measured to biologically characterize the clinical clusters. Five clinical clusters were identified, including two characterized by high pack-year exposure to cigarette smoking and low FEV1/FVC. There were marked differences between the two clusters of cigarette smokers. One had high levels of circulating eosinophils, high IgE levels, and a high sinus disease score. The other was characterized by low levels of the same parameters. Sputum analysis revealed increased levels of IL-5 in the former cluster and increased levels of IL-6 and osteopontin in the latter. The other three clusters were similar to those previously reported: young onset/atopic, nonsmoker/less eosinophilic, and female/obese. Key clinical variables were confirmed to be stable and consistent 1 year later. This study reveals two distinct phenotypes of severe asthma in current and former cigarette smokers with potentially different biological pathways contributing to fixed airflow limitation. Clinical trial registered with www.umin.ac.jp (000003254).

  19. The genetics of alcoholism: identifying specific genes through family studies.

    Science.gov (United States)

    Edenberg, Howard J; Foroud, Tatiana

    2006-09-01

    Alcoholism is a complex disorder with both genetic and environmental risk factors. Studies in humans have begun to elucidate the genetic underpinnings of the risk for alcoholism. Here we briefly review strategies for identifying individual genes in which variations affect the risk for alcoholism and related phenotypes, in the context of one large study that has successfully identified such genes. The Collaborative Study on the Genetics of Alcoholism (COGA) is a family-based study that has collected detailed phenotypic data on individuals in families with multiple alcoholic members. A genome-wide linkage approach led to the identification of chromosomal regions containing genes that influenced alcoholism risk and related phenotypes. Subsequently, single nucleotide polymorphisms (SNPs) were genotyped in positional candidate genes located within the linked chromosomal regions, and analyzed for association with these phenotypes. Using this sequential approach, COGA has detected association with GABRA2, CHRM2 and ADH4; these associations have all been replicated by other researchers. COGA has detected association to additional genes including GABRG3, TAS2R16, SNCA, OPRK1 and PDYN, results that are awaiting confirmation. These successes demonstrate that genes contributing to the risk for alcoholism can be reliably identified using human subjects.

  20. Identifying gene regulatory network rewiring using latent differential graphical models.

    Science.gov (United States)

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-09-30

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions.

  1. Identifying influential individuals on intensive care units: using cluster analysis to explore culture.

    Science.gov (United States)

    Fong, Allan; Clark, Lindsey; Cheng, Tianyi; Franklin, Ella; Fernandez, Nicole; Ratwani, Raj; Parker, Sarah Henrickson

    2017-07-01

    The objective of this paper is to identify attribute patterns of influential individuals in intensive care units using unsupervised cluster analysis. Despite the acknowledgement that culture of an organisation is critical to improving patient safety, specific methods to shift culture have not been explicitly identified. A social network analysis survey was conducted and an unsupervised cluster analysis was used. A total of 100 surveys were gathered. Unsupervised cluster analysis was used to group individuals with similar dimensions highlighting three general genres of influencers: well-rounded, knowledge and relational. Culture is created locally by individual influencers. Cluster analysis is an effective way to identify common characteristics among members of an intensive care unit team that are noted as highly influential by their peers. To change culture, identifying and then integrating the influencers in intervention development and dissemination may create more sustainable and effective culture change. Additional studies are ongoing to test the effectiveness of utilising these influencers to disseminate patient safety interventions. This study offers an approach that can be helpful in both identifying and understanding influential team members and may be an important aspect of developing methods to change organisational culture. © 2017 John Wiley & Sons Ltd.

  2. Distribution of Suicin Gene Clusters in Streptococcus suis Serotype 2 Belonging to Sequence Types 25 and 28

    Directory of Open Access Journals (Sweden)

    Taryn B. T. Athey

    2016-01-01

    Full Text Available Recently, we reported the purification and characterization of three distinct lantibiotics (named suicin 90-1330, suicin 3908, and suicin 65 produced by Streptococcus suis. In this study, we investigated the distribution of the three suicin lantibiotic gene clusters among serotype 2 S. suis strains belonging to sequence type (ST 25 and ST28, the two dominant STs identified in North America. The genomes of 102 strains were interrogated for the presence of suicin gene clusters encoding suicins 90-1330, 3908, and 65. The gene cluster encoding suicin 65 was the most prevalent and mainly found among ST25 strains. In contrast, none of the genes related to suicin 90-1330 production were identified in 51 ST25 strains nor in 35/51 ST28 strains. However, the complete suicin 90-1330 gene cluster was found in ten ST28 strains, although some genes in the cluster were truncated in three of these isolates. The vast majority (101/102 of S. suis strains did not possess any of the genes encoding suicin 3908. In conclusion, this study indicates heterogeneous distribution of suicin genes in S. suis.

  3. 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 product......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......, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally...

  4. Comparative genomic analysis of sixty mycobacteriophage genomes: Genome clustering, gene acquisition and gene size

    Science.gov (United States)

    Hatfull, Graham F.; Jacobs-Sera, Deborah; Lawrence, Jeffrey G.; Pope, Welkin H.; Russell, Daniel A.; Ko, Ching-Chung; Weber, Rebecca J.; Patel, Manisha C.; Germane, Katherine L.; Edgar, Robert H.; Hoyte, Natasha N.; Bowman, Charles A.; Tantoco, Anthony T.; Paladin, Elizabeth C.; Myers, Marlana S.; Smith, Alexis L.; Grace, Molly S.; Pham, Thuy T.; O'Brien, Matthew B.; Vogelsberger, Amy M.; Hryckowian, Andrew J.; Wynalek, Jessica L.; Donis-Keller, Helen; Bogel, Matt W.; Peebles, Craig L.; Cresawn, Steve G.; Hendrix, Roger W.

    2010-01-01

    Mycobacteriophages are viruses that infect mycobacterial hosts. Expansion of a collection of sequenced phage genomes to a total of sixty – all infecting a common bacterial host – provides further insight into their diversity and evolution. Of the sixty phage genomes, 55 can be grouped into nine clusters according to their nucleotide sequence similarities, five of which can be further divided into subclusters; five genomes do not cluster with other phages. The sequence diversity between genomes within a cluster varies greatly; for example, the six genomes in cluster D share more than 97.5% average nucleotide similarity with each other. In contrast, similarity between the two genomes in Cluster I is barely detectable by diagonal plot analysis. The total of 6,858 predicted ORFs have been grouped into 1523 phamilies (phams) of related sequences, 46% of which possess only a single member. Only 18.8% of the phams have sequence similarity to non-mycobacteriophage database entries and fewer than 10% of all phams can be assigned functions based on database searching or synteny. Genome clustering facilitates the identification of genes that are in greatest genetic flux and are more likely to have been exchanged horizontally in relatively recent evolutionary time. Although mycobacteriophage genes exhibit smaller average size than genes of their host (205 residues compared to 315), phage genes in higher flux average only ∼100 amino acids, suggesting that the primary units of genetic exchange correspond to single protein domains. PMID:20064525

  5. Mapping gene clusters within arrayed metagenomic libraries to expand the structural diversity of biomedically relevant natural products.

    Science.gov (United States)

    Owen, Jeremy G; Reddy, Boojala Vijay B; Ternei, Melinda A; Charlop-Powers, Zachary; Calle, Paula Y; Kim, Jeffrey H; Brady, Sean F

    2013-07-16

    Complex microbial ecosystems contain large reservoirs of unexplored biosynthetic diversity. Here we provide an experimental framework and data analysis tool to facilitate the targeted discovery of natural-product biosynthetic gene clusters from the environment. Multiplex sequencing of barcoded PCR amplicons is followed by sequence similarity directed data parsing to identify sequences bearing close resemblance to biosynthetically or biomedically interesting gene clusters. Amplicons are then mapped onto arrayed metagenomic libraries to guide the recovery of targeted gene clusters. When applied to adenylation- and ketosynthase-domain amplicons derived from saturating soil DNA libraries, our analysis pipeline led to the recovery of biosynthetic clusters predicted to encode for previously uncharacterized glycopeptide- and lipopeptide-like antibiotics; thiocoraline-, azinomycin-, and bleomycin-like antitumor agents; and a rapamycin-like immunosuppressant. The utility of the approach is demonstrated by using recovered eDNA sequences to generate glycopeptide derivatives. The experiments described here constitute a systematic interrogation of a soil metagenome for gene clusters capable of encoding naturally occurring derivatives of biomedically relevant natural products. Our results show that previously undetected biosynthetic gene clusters with potential biomedical relevance are very common in the environment. This general process should permit the routine screening of environmental samples for gene clusters capable of encoding the systematic expansion of the structural diversity seen in biomedically relevant families of natural products.

  6. Genome scan identifies a locus affecting gamma-globin expression in human beta-cluster YAC transgenic mice

    Energy Technology Data Exchange (ETDEWEB)

    Lin, S.D.; Cooper, P.; Fung, J.; Weier, H.U.G.; Rubin, E.M.

    2000-03-01

    Genetic factors affecting post-natal g-globin expression - a major modifier of the severity of both b-thalassemia and sickle cell anemia, have been difficult to study. This is especially so in mice, an organism lacking a globin gene with an expression pattern equivalent to that of human g-globin. To model the human b-cluster in mice, with the goal of screening for loci affecting human g-globin expression in vivo, we introduced a human b-globin cluster YAC transgene into the genome of FVB mice . The b-cluster contained a Greek hereditary persistence of fetal hemoglobin (HPFH) g allele resulting in postnatal expression of human g-globin in transgenic mice. The level of human g-globin for various F1 hybrids derived from crosses between the FVB transgenics and other inbred mouse strains was assessed. The g-globin level of the C3HeB/FVB transgenic mice was noted to be significantly elevated. To map genes affecting postnatal g-globin expression, a 20 centiMorgan (cM) genome scan of a C3HeB/F VB transgenics [prime] FVB backcross was performed, followed by high-resolution marker analysis of promising loci. From this analysis we mapped a locus within a 2.2 cM interval of mouse chromosome 1 at a LOD score of 4.2 that contributes 10.4% of variation in g-globin expression level. Combining transgenic modeling of the human b-globin gene cluster with quantitative trait analysis, we have identified and mapped a murine locus that impacts on human g-globin expression in vivo.

  7. 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.

  8. Cluster Analysis and Significance of Novel Genes Related to Molecular Classification of Glioma

    Institute of Scientific and Technical Information of China (English)

    Juxiang Chen; Yicheng Lu; Guohan Hu; Kehua Sun; Chun Luo; Meiqing Lou; Kang Ying; Yao Li

    2005-01-01

    OBJECTIVE To screen differentially expressed genes in the development of human glioma and establish a primary molecular classification of glioma based on gene expression using cDNA microarrays.METHODS Brain specimens were obtained from 18 patients with glioma, 10males and 8 females, ages 14~62 with an average age of 44.4. The total RNAs of these glioma specimens and two specimens of donated brain of normal adults were extracted. BioStarH140S microarrays (including 8,347old genes and 5,592 novel genes) were adopted and hybridized with probes which were prepared from the total RNAs. Differentially expressed genes between normal tissues and glioma tissues were assayed after scanning cDNA microarrays with ScanArray4000. Northern hybridization and in situ hybridization (ISH) were used to identify functions of novel genes. Those differentially expressed genes were studied with a Hierarchical method and molecular classification of glioma was preliminary carried out.RESULTS Among the 13,939 target genes, there were 1,200 (8.61%)differentially expressed genes, of which 395 (2.83%) were novel genes. A total of 348 genes were up-regulated and 852 genes were down-regulated in the gliomas. The results of bioinformatical analysis, Northern hybridization and ISH revealed that those novel genes were highly associated with gliomas. There were multiple genes, such as the MAP gene、cytoskeleton & matrix motility genes, etc, which were of relevance to classification by the Hierarchical method. Molecular classification of glioma using a Hierarchical cluster was in accordance with pathology and suggested a molecular process of tumorigenesis and development.CONCLUSION Multiple genes play important roles in development of glioma. cDNA microarray technology is a powerful technique in screening for differentially expressed genes between two different kinds of tissues. Further analysis of gene expression and novel genes would be helpful to understand the molecular mechanism of glioma

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

    OpenAIRE

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

    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...

  10. Cloning large natural product gene clusters from the environment: Piecing environmental DNA gene clusters back together with TAR

    OpenAIRE

    Kim, Jeffrey H.; Feng, Zhiyang; Bauer, John D.; Kallifidas, Dimitris; Calle, Paula Y.; Brady, Sean F

    2010-01-01

    A single gram of soil can contain thousands of unique bacterial species, of which only a small fraction is regularly cultured in the laboratory. Although the fermentation of cultured microorganisms has provided access to numerous bioactive secondary metabolites, with these same methods it is not possible to characterize the natural products encoded by the uncultured majority. The heterologous expression of biosynthetic gene clusters cloned from DNA extracted directly from environmental sample...

  11. Stable Voice Clusters Identified When Using the Maximum versus Minimum Intensity Curve in the Phonetogram.

    Science.gov (United States)

    Camarrone, Flavio; Ivanova, Anna; Decoster, Wivine; de Jong, Felix; van Hulle, Marc M

    2015-01-01

    To examine whether the minimum as well as the maximum voice intensity (i.e. sound pressure level, SPL) curves of a voice range profile (VRP) are required when discovering different voice groups based on a clustering analysis. In this approach, no a priori labeling of voice types is used. VRPs of 194 (84 male and 110 female) professional singers were registered and processed. Cluster analysis was performed with the use of features related to (1) both the maximum and minimum SPL curves and (2) the maximum SPL curve only. Features related to the maximum as well as the minimum SPL curves showed three clusters in both male and female voices. These clusters, or voice groups, are based on voice types with similar VRP features. However, when using features related only to the maximum SPL curve, the clusters became less obvious. Features related to the maximum and minimum SPL curves of a VRP are both needed in order to identify the three voice clusters. © 2016 S. Karger AG, Basel.

  12. Fast Gene Ontology based clustering for microarray experiments

    OpenAIRE

    Ovaska Kristian; Laakso Marko; Hautaniemi Sampsa

    2008-01-01

    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 fa...

  13. Evaluation of potential regulatory elements identified as DNase I hypersensitive sites in the CFTR gene

    DEFF Research Database (Denmark)

    Phylactides, M.; Rowntree, R.; Nuthall, H.

    2002-01-01

    The cystic fibrosis transmembrane conductance regulator (CFTR) gene shows a complex pattern of expression, with temporal and spatial regulation that is not accounted for by elements in the promoter. One approach to identifying the regulatory elements for CFTR is the mapping of DNase I...... hypersensitive sites (DHS) within the locus. We previously identified at least 12 clusters of DHS across the CFTR gene and here further evaluate DHS in introns 2,3,10,16,17a, 18, 20 and 21 to assess their functional importance in regulation of CFTR gene expression. Transient transfections of enhancer....../reporter constructs containing the DHS regions showed that those in introns 20 and 21 augmented the activity of the CFTR promoter. Structural analysis of the DNA sequence at the DHS suggested that only the one intron 21 might be caused by inherent DNA structures. Cell specificity of the DHS suggested a role...

  14. 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...... identified, and polyketide synthase and non-ribosomal peptide synthetase based BGCs were grouped into gene cluster families and mapped to known pathways. The grouping of BGCs allowed us to study the evolutionary trajectory of pathways based on 6-methylsalicylic acid (6-MSA) synthases. Finally, we cross...

  15. 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.

  16. GenClust: a genetic algorithm for clustering gene expression data.

    Science.gov (United States)

    Di Gesú, Vito; Giancarlo, Raffaele; Lo Bosco, Giosué; Raimondi, Alessandra; Scaturro, Davide

    2005-12-07

    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. 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. 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.

  17. MIDDAS-M: motif-independent de novo detection of secondary metabolite gene clusters through the integration of genome sequencing and transcriptome data.

    Science.gov (United States)

    Umemura, Myco; Koike, Hideaki; Nagano, Nozomi; Ishii, Tomoko; Kawano, Jin; Yamane, Noriko; Kozone, Ikuko; Horimoto, Katsuhisa; Shin-ya, Kazuo; Asai, Kiyoshi; Yu, Jiujiang; Bennett, Joan W; Machida, Masayuki

    2013-01-01

    Many bioactive natural products are produced as "secondary metabolites" by plants, bacteria, and fungi. During the middle of the 20th century, several secondary metabolites from fungi revolutionized the pharmaceutical industry, for example, penicillin, lovastatin, and cyclosporine. They are generally biosynthesized by enzymes encoded by clusters of coordinately regulated genes, and several motif-based methods have been developed to detect secondary metabolite biosynthetic (SMB) gene clusters using the sequence information of typical SMB core genes such as polyketide synthases (PKS) and non-ribosomal peptide synthetases (NRPS). However, no detection method exists for SMB gene clusters that are functional and do not include core SMB genes at present. To advance the exploration of SMB gene clusters, especially those without known core genes, we developed MIDDAS-M, a motif-independent de novodetection algorithm for SMB gene clusters. We integrated virtual gene cluster generation in an annotated genome sequence with highly sensitive scoring of the cooperative transcriptional regulation of cluster member genes. MIDDAS-M accurately predicted 38 SMB gene clusters that have been experimentally confirmed and/or predicted by other motif-based methods in 3 fungal strains. MIDDAS-M further identified a new SMB gene cluster for ustiloxin B, which was experimentally validated. Sequence analysis of the cluster genes indicated a novel mechanism for peptide biosynthesis independent of NRPS. Because it is fully computational and independent of empirical knowledge about SMB core genes, MIDDAS-M allows a large-scale, comprehensive analysis of SMB gene clusters, including those with novel biosynthetic mechanisms that do not contain any functionally characterized genes.

  18. Contemporary Approaches for Identifying Rare Bone Disease Causing Genes

    Institute of Scientific and Technical Information of China (English)

    Charles R.Farber; Thomas L.Clemens

    2013-01-01

    Recent improvements in the speed and accuracy of DNA sequencing, together with increasingly sophisti-cated mathematical approaches for annotating gene networks, have revolutionized the field of human genetics and made these once time consuming approaches assessable to most investigators. In the field of bone research, a particularly active area of gene discovery has occurred in patients with rare bone disorders such as osteogenesis imperfecta (OI) that are caused by mutations in single genes. In this perspective, we highlight some of these technological advances and describe how they have been used to identify the genetic determinants underlying two previously unexplained cases of OI. The widespread availability of advanced methods for DNA sequencing and bioinformatics analysis can be expected to greatly facilitate identification of novel gene networks that normally function to control bone formation and maintenance.

  19. Fetal Haemoglobin and β-globin Gene Cluster Haplotypes among Sickle Cell Patients in Chhattisgarh

    OpenAIRE

    Bhagat, Sanjana; Patra, Pradeep Kumar; Thakur, Amar Singh

    2013-01-01

    Background: Foetal Haemoglobin (HbF) is the best-known genetic modulator of sickle cell anaemia, which varies dramatically in concentration in the blood of these patients. The patients with SCA display a remarkable variability in the disease severity. High HbF levels and the β-globin gene cluster haplotypes influence the clinical presentation of sickle cell disease. To identify the genetic modifiers which influence the disease severity, we conducted a β-globin haplotype analysis in the sickle...

  20. Using Light-at-Night (LAN) Satellite Data for Identifying Clusters of Economic Activities in Europe

    Science.gov (United States)

    Rybnikova, N. A.; Portnov, B. A.

    2015-04-01

    Enterprises organized in clusters are often efficient in stimulating urban development, productivity and profit outflows. Identifying clusters of economic activities (EAs) thus becomes an important step in devising regional development policies, aimed at facilitating regional economic development. However, a major problem with cluster identification stems from limited reporting of specific EAs by individual countries and administrative entities. Even Eurostat, which maintains most advances regional databases, provides data for less than 50% of all regional subdivisions of the 3rd tier of the Nomenclature of Territorial Units for Statistics (NUTS3). Such poor reporting impedes identification of EA clusters and economic forces behind them. In this study, we test a possibility that missing data on geographic concentrations of EAs can be reconstructed using Light-at-Night (LAN) satellite measurements, and that such reconstructed data can then be used for the identification of EA clusters. As we hypothesize, LAN, captured by satellite sensors, is characterized by different intensity, depending on its source - production facilities, services, etc., - and this information can be used for EA identification. The study was carried out in three stages. First, using nighttime satellite images, we determined what types of EAs can be identified, with a sufficient degree of accuracy, by LAN they emit. Second, we calculated multivariate statistical models, linking EAs concentrations with LAN intensities and several locational and development attributes of NUTS3 regions in Europe. Next, using the obtained statistical models, we restored missing data on EAs across NUTS3 regions in Europe and identified clusters of EAs, using spatial analysis tools.

  1. Engineered Streptomyces avermitilis host for heterologous expression of biosynthetic gene cluster for secondary metabolites.

    Science.gov (United States)

    Komatsu, Mamoru; Komatsu, Kyoko; Koiwai, Hanae; Yamada, Yuuki; Kozone, Ikuko; Izumikawa, Miho; Hashimoto, Junko; Takagi, Motoki; Omura, Satoshi; Shin-ya, Kazuo; Cane, David E; Ikeda, Haruo

    2013-07-19

    An industrial microorganism, Streptomyces avermitilis, which is a producer of anthelmintic macrocyclic lactones, avermectins, has been constructed as a versatile model host for heterologous expression of genes encoding secondary metabolite biosynthesis. Twenty of the entire biosynthetic gene clusters for secondary metabolites were successively cloned and introduced into a versatile model host S. avermitilis SUKA17 or 22. Almost all S. avermitilis transformants carrying the entire gene cluster produced metabolites as a result of the expression of biosynthetic gene clusters introduced. A few transformants were unable to produce metabolites, but their production was restored by the expression of biosynthetic genes using an alternative promoter or the expression of a regulatory gene in the gene cluster that controls the expression of biosynthetic genes in the cluster using an alternative promoter. Production of metabolites in some transformants of the versatile host was higher than that of the original producers, and cryptic biosynthetic gene clusters in the original producer were also expressed in a versatile host.

  2. Metabolic diversification--independent assembly of operon-like gene clusters in different plants.

    Science.gov (United States)

    Field, Ben; Osbourn, Anne E

    2008-04-25

    Operons are clusters of unrelated genes with related functions that are a feature of prokaryotic genomes. Here, we report on an operon-like gene cluster in the plant Arabidopsis thaliana that is required for triterpene synthesis (the thalianol pathway). The clustered genes are coexpressed, as in bacterial operons. However, despite the resemblance to a bacterial operon, this gene cluster has been assembled from plant genes by gene duplication, neofunctionalization, and genome reorganization, rather than by horizontal gene transfer from bacteria. Furthermore, recent assembly of operon-like gene clusters for triterpene synthesis has occurred independently in divergent plant lineages (Arabidopsis and oat). Thus, selection pressure may act during the formation of certain plant metabolic pathways to drive gene clustering.

  3. Functional epigenomics identifies genes frequently silenced in prostate cancer.

    Science.gov (United States)

    Lodygin, Dimitri; Epanchintsev, Alexey; Menssen, Antje; Diebold, Joachim; Hermeking, Heiko

    2005-05-15

    In many cases, silencing of gene expression by CpG methylation is causally involved in carcinogenesis. Furthermore, cancer-specific CpG methylation may serve as a tumor marker. In order to identify candidate genes for inactivation by CpG methylation in prostate cancer, the prostate cancer cell lines LNCaP, PC3, and Du-145 were treated with 5-aza-2' deoxycytidine and trichostatin A, which leads to reversion of epigenetic silencing. By microarray analysis of 18,400 individual transcripts, several hundred genes were found to be induced when compared with cells treated with trichostatin A. Fifty re-expressed genes were selected for further analysis based on their known function, which implied a possible involvement in tumor suppression. Twelve of these genes showed a significant degree of CpG methylation in their promoters. Six genes were silenced by CpG methylation in the majority of five analyzed prostate cancer cell lines, although they displayed robust mRNA expression in normal prostate epithelial cells obtained from four different donors. In primary prostate cancer samples derived from 41 patients, the frequencies of CpG methylation detected in the promoter regions of these genes were: GPX3, 93%; SFRP1, 83%; COX2, 78%; DKK3, 68%; GSTM1, 58%; and KIP2/p57, 56%. Ectopic expression of SFRP1 or DKK3 resulted in decreased proliferation. The expression of DKK3 was accompanied by attenuation of the mitogen-activated protein kinase pathway. The high frequency of CpG methylation detected in the promoters of the identified genes suggests a potential causal involvement in prostate cancer and may prove useful for diagnostic purposes.

  4. Cluster analysis for identifying sub-groups and selecting potential discriminatory variables in human encephalitis

    Directory of Open Access Journals (Sweden)

    Crowcroft Natasha S

    2010-12-01

    Full Text Available Abstract Background Encephalitis is an acute clinical syndrome of the central nervous system (CNS, often associated with fatal outcome or permanent damage, including cognitive and behavioural impairment, affective disorders and epileptic seizures. Infection of the central nervous system is considered to be a major cause of encephalitis and more than 100 different pathogens have been recognized as causative agents. However, a large proportion of cases have unknown disease etiology. Methods We perform hierarchical cluster analysis on a multicenter England encephalitis data set with the aim of identifying sub-groups in human encephalitis. We use the simple matching similarity measure which is appropriate for binary data sets and performed variable selection using cluster heatmaps. We also use heatmaps to visually assess underlying patterns in the data, identify the main clinical and laboratory features and identify potential risk factors associated with encephalitis. Results Our results identified fever, personality and behavioural change, headache and lethargy as the main characteristics of encephalitis. Diagnostic variables such as brain scan and measurements from cerebrospinal fluids are also identified as main indicators of encephalitis. Our analysis revealed six major clusters in the England encephalitis data set. However, marked within-cluster heterogeneity is observed in some of the big clusters indicating possible sub-groups. Overall, the results show that patients are clustered according to symptom and diagnostic variables rather than causal agents. Exposure variables such as recent infection, sick person contact and animal contact have been identified as potential risk factors. Conclusions It is in general assumed and is a common practice to group encephalitis cases according to disease etiology. However, our results indicate that patients are clustered with respect to mainly symptom and diagnostic variables rather than causal agents

  5. 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.

  6. Identifying coherent structures and vortex clusters in Taylor-Couette turbulence

    Science.gov (United States)

    Spandan, Vamsi; Ostilla-Monico, Rodolfo; Lohse, Detlef; Verzicco, Roberto

    2016-04-01

    The nature of the underlying structures in Taylor-Couette (TC) flow, the flow between two co-axial and independently rotating cylinders is investigated by two methods. First, the quadrant analysis technique for identifying structures with intense radial-azimuthal stresses (also referred to as ‘Q’s) of Lozano-Durán et al., (J. Fluid Mech. 694, 100-130) is used to identify the main structures responsible for the transport of angular velocity. Second, the vortex clusters are identified based on the analysis by del Álamo et al., (J. Fluid. Mech., 561, 329-358). In order to test these criteria, two different radius ratios η = ri/ro are considered, where ri and ro are the radii of inner and outer cylinder, respectively: (i) η = 0.5 and (ii) η = 0.909, which correspond to high and low curvature geometries, respectively and have different underlying structures. The Taylor rolls, i.e. the large-scale coherent structures, are effectively captured as ‘Q’s for the low curvature setup and it is observed that curvature plays a dominant role in influencing the size and volumes of these ‘Q’s. On the other hand, the vortex clusters are smaller in size when compared to the ‘Q’ structures. These vortex clusters are found to be taller in the case of η = 0.909, while the distribution of the lengths of these clusters is almost homogenous for both radius ratios.

  7. Phenotype-Dependent Coexpression Gene Clusters: Application to Normal and Premature Ageing.

    Science.gov (United States)

    Wang, Kun; Das, Avinash; Xiong, Zheng-Mei; Cao, Kan; Hannenhalli, Sridhar

    2015-01-01

    Hutchinson Gilford progeria syndrome (HGPS) is a rare genetic disease with symptoms of aging at a very early age. Its molecular basis is not entirely clear, although profound gene expression changes have been reported, and there are some known and other presumed overlaps with normal aging process. Identification of genes with agingor HGPS-associated expression changes is thus an important problem. However, standard regression approaches are currently unsuitable for this task due to limited sample sizes, thus motivating development of alternative approaches. Here, we report a novel iterative multiple regression approach that leverages co-expressed gene clusters to identify gene clusters whose expression co-varies with age and/or HGPS. We have applied our approach to novel RNA-seq profiles in fibroblast cell cultures at three different cellular ages, both from HGPS patients and normal samples. After establishing the robustness of our approach, we perform a comparative investigation of biological processes underlying normal aging and HGPS. Our results recapitulate previously known processes underlying aging as well as suggest numerous unique processes underlying aging and HGPS. The approach could also be useful in detecting phenotype-dependent co-expression gene clusters in other contexts with limited sample sizes.

  8. Evolution of coding and non-coding genes in HOX clusters of a marsupial

    Directory of Open Access Journals (Sweden)

    Yu Hongshi

    2012-06-01

    Full Text Available Abstract Background The HOX gene clusters are thought to be highly conserved amongst mammals and other vertebrates, but the long non-coding RNAs have only been studied in detail in human and mouse. The sequencing of the kangaroo genome provides an opportunity to use comparative analyses to compare the HOX clusters of a mammal with a distinct body plan to those of other mammals. Results Here we report a comparative analysis of HOX gene clusters between an Australian marsupial of the kangaroo family and the eutherians. There was a strikingly high level of conservation of HOX gene sequence and structure and non-protein coding genes including the microRNAs miR-196a, miR-196b, miR-10a and miR-10b and the long non-coding RNAs HOTAIR, HOTAIRM1 and HOXA11AS that play critical roles in regulating gene expression and controlling development. By microRNA deep sequencing and comparative genomic analyses, two conserved microRNAs (miR-10a and miR-10b were identified and one new candidate microRNA with typical hairpin precursor structure that is expressed in both fibroblasts and testes was found. The prediction of microRNA target analysis showed that several known microRNA targets, such as miR-10, miR-414 and miR-464, were found in the tammar HOX clusters. In addition, several novel and putative miRNAs were identified that originated from elsewhere in the tammar genome and that target the tammar HOXB and HOXD clusters. Conclusions This study confirms that the emergence of known long non-coding RNAs in the HOX clusters clearly predate the marsupial-eutherian divergence 160 Ma ago. It also identified a new potentially functional microRNA as well as conserved miRNAs. These non-coding RNAs may participate in the regulation of HOX genes to influence the body plan of this marsupial.

  9. Identifying genes for neurobehavioural traits in rodents: progress and pitfalls

    Directory of Open Access Journals (Sweden)

    Amelie Baud

    2017-04-01

    Full Text Available Identifying genes and pathways that contribute to differences in neurobehavioural traits is a key goal in psychiatric research. Despite considerable success in identifying quantitative trait loci (QTLs associated with behaviour in laboratory rodents, pinpointing the causal variants and genes is more challenging. For a long time, the main obstacle was the size of QTLs, which could encompass tens if not hundreds of genes. However, recent studies have exploited mouse and rat resources that allow mapping of phenotypes to narrow intervals, encompassing only a few genes. Here, we review these studies, showcase the rodent resources they have used and highlight the insights into neurobehavioural traits provided to date. We discuss what we see as the biggest challenge in the field – translating QTLs into biological knowledge by experimentally validating and functionally characterizing candidate genes – and propose that the CRISPR/Cas genome-editing system holds the key to overcoming this obstacle. Finally, we challenge traditional views on inbred versus outbred resources in the light of recent resource and technology developments.

  10. Identifying genes for neurobehavioural traits in rodents: progress and pitfalls.

    Science.gov (United States)

    Baud, Amelie; Flint, Jonathan

    2017-04-01

    Identifying genes and pathways that contribute to differences in neurobehavioural traits is a key goal in psychiatric research. Despite considerable success in identifying quantitative trait loci (QTLs) associated with behaviour in laboratory rodents, pinpointing the causal variants and genes is more challenging. For a long time, the main obstacle was the size of QTLs, which could encompass tens if not hundreds of genes. However, recent studies have exploited mouse and rat resources that allow mapping of phenotypes to narrow intervals, encompassing only a few genes. Here, we review these studies, showcase the rodent resources they have used and highlight the insights into neurobehavioural traits provided to date. We discuss what we see as the biggest challenge in the field - translating QTLs into biological knowledge by experimentally validating and functionally characterizing candidate genes - and propose that the CRISPR/Cas genome-editing system holds the key to overcoming this obstacle. Finally, we challenge traditional views on inbred versus outbred resources in the light of recent resource and technology developments. © 2017. Published by The Company of Biologists Ltd.

  11. Data Preprocessing in Cluster Analysis of Gene Expression

    Institute of Scientific and Technical Information of China (English)

    杨春梅; 万柏坤; 高晓峰

    2003-01-01

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

  12. Genome mining of the hitachimycin biosynthetic gene cluster: involvement of a phenylalanine-2,3-aminomutase in biosynthesis.

    Science.gov (United States)

    Kudo, Fumitaka; Kawamura, Koichi; Uchino, Asuka; Miyanaga, Akimasa; Numakura, Mario; Takayanagi, Ryuichi; Eguchi, Tadashi

    2015-04-13

    Hitachimycin is a macrolactam antibiotic with (S)-β-phenylalanine (β-Phe) at the starter position of its polyketide skeleton. To understand the incorporation mechanism of β-Phe and the modification mechanism of the unique polyketide skeleton, the biosynthetic gene cluster for hitachimycin in Streptomyces scabrisporus was identified by genome mining. The identified gene cluster contains a putative phenylalanine-2,3-aminomutase (PAM), five polyketide synthases, four β-amino-acid-carrying enzymes, and a characteristic amidohydrolase. A hitA knockout mutant showed no hitachimycin production, but antibiotic production was restored by feeding with (S)-β-Phe. We also confirmed the enzymatic activity of the HitA PAM. The results suggest that the identified gene cluster is responsible for the biosynthesis of hitachimycin. A plausible biosynthetic pathway for hitachimycin, including a unique polyketide skeletal transformation mechanism, is proposed.

  13. Using earthquake clusters to identify fracture zones at Puna geothermal field, Hawaii

    Science.gov (United States)

    Lucas, A.; Shalev, E.; Malin, P.; Kenedi, C. L.

    2010-12-01

    The actively producing Puna geothermal system (PGS) is located on the Kilauea East Rift Zone (ERZ), which extends out from the active Kilauea volcano on Hawaii. In the Puna area the rift trend is identified as NE-SW from surface expressions of normal faulting with a corresponding strike; at PGS the surface expression offsets in a left step, but no rift perpendicular faulting is observed. An eight station borehole seismic network has been installed in the area of the geothermal system. Since June 2006, a total of 6162 earthquakes have been located close to or inside the geothermal system. The spread of earthquake locations follows the rift trend, but down rift to the NE of PGS almost no earthquakes are observed. Most earthquakes located within the PGS range between 2-3 km depth. Up rift to the SW of PGS the number of events decreases and the depth range increases to 3-4 km. All initial locations used Hypoinverse71 and showed no trends other than the dominant rift parallel. Double difference relocation of all earthquakes, using both catalog and cross-correlation, identified one large cluster but could not conclusively identify trends within the cluster. A large number of earthquake waveforms showed identifiable shear wave splitting. For five stations out of the six where shear wave splitting was observed, the dominant polarization direction was rift parallel. Two of the five stations also showed a smaller rift perpendicular signal. The sixth station (located close to the area of the rift offset) displayed a N-S polarization, approximately halfway between rift parallel and perpendicular. The shear wave splitting time delays indicate that fracture density is higher at the PGS compared to the surrounding ERZ. Correlation co-efficient clustering with independent P and S wave windows was used to identify clusters based on similar earthquake waveforms. In total, 40 localized clusters containing ten or more events were identified. The largest cluster was located in the

  14. Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering

    Science.gov (United States)

    Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

    2013-01-01

    Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node’s neighbors but do not directly make use of the interactions among it’s neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors’ influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about nodes, more than 15 times faster than PageRank. PMID:24204833

  15. Identifying disease feature genes based on cellular localized gene functional modules and regulation networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Min; ZHU Jing; GUO Zheng; LI Xia; YANG Da; WANG Lei; RAO Shaoqi

    2006-01-01

    Identifying disease-relevant genes and functional modules, based on gene expression profiles and gene functional knowledge, is of high importance for studying disease mechanisms and subtyping disease phenotypes. Using gene categories of biological process and cellular component in Gene Ontology, we propose an approach to selecting functional modules enriched with differentially expressed genes, and identifying the feature functional modules of high disease discriminating abilities. Using the differentially expressed genes in each feature module as the feature genes, we reveal the relevance of the modules to the studied diseases. Using three datasets for prostate cancer, gastric cancer, and leukemia, we have demonstrated that the proposed modular approach is of high power in identifying functionally integrated feature gene subsets that are highly relevant to the disease mechanisms. Our analysis has also shown that the critical disease-relevant genes might be better recognized from the gene regulation network, which is constructed using the characterized functional modules, giving important clues to the concerted mechanisms of the modules responding to complex disease states. In addition, the proposed approach to selecting the disease-relevant genes by jointly considering the gene functional knowledge suggests a new way for precisely classifying disease samples with clear biological interpretations, which is critical for the clinical diagnosis and the elucidation of the pathogenic basis of complex diseases.

  16. Expression Profiling Identifies Candidate Genes for Fiber Yield and Quality

    Institute of Scientific and Technical Information of China (English)

    LLEWELLYN D J; MACHADO A; AI-GHAZI Y; WU Y; DENNIS E S

    2008-01-01

    @@ Gene expression profiling at early stages (0~2 DPA) of fiber development in Gossypiurn hirsuturn identified a number of transcription factors which were down regulated in fiberless mutants relative to wild type controls and which could play a role in controlling early fiber development.Chief among these was GhMYB25,a Mixta-like MYB gene.Transgenic GhMYB25-silenced cotton showeddramatic alterations in fiber initiation and the timing of rapid fiber elongation,reduction in trichomes on other parts of the plant,a delay in lateral root growth,and a reduction in seed production due toreduced fertilization efficiency.

  17. Expanding our understanding of sequence-function relationships of type II polyketide biosynthetic gene clusters: bioinformatics-guided identification of Frankiamicin A from Frankia sp. EAN1pec.

    Directory of Open Access Journals (Sweden)

    Yasushi Ogasawara

    Full Text Available A large and rapidly increasing number of unstudied "orphan" natural product biosynthetic gene clusters are being uncovered in sequenced microbial genomes. An important goal of modern natural products research is to be able to accurately predict natural product structures and biosynthetic pathways from these gene cluster sequences. This requires both development of bioinformatic methods for global analysis of these gene clusters and experimental characterization of select products produced by gene clusters with divergent sequence characteristics. Here, we conduct global bioinformatic analysis of all available type II polyketide gene cluster sequences and identify a conserved set of gene clusters with unique ketosynthase α/β sequence characteristics in the genomes of Frankia species, a group of Actinobacteria with underexploited natural product biosynthetic potential. Through LC-MS profiling of extracts from several Frankia species grown under various conditions, we identified Frankia sp. EAN1pec as producing a compound with spectral characteristics consistent with the type II polyketide produced by this gene cluster. We isolated the compound, a pentangular polyketide which we named frankiamicin A, and elucidated its structure by NMR and labeled precursor feeding. We also propose biosynthetic and regulatory pathways for frankiamicin A based on comparative genomic analysis and literature precedent, and conduct bioactivity assays of the compound. Our findings provide new information linking this set of Frankia gene clusters with the compound they produce, and our approach has implications for accurate functional prediction of the many other type II polyketide clusters present in bacterial genomes.

  18. Using SCOPE to identify potential regulatory motifs in coregulated genes.

    Science.gov (United States)

    Martyanov, Viktor; Gross, Robert H

    2011-05-31

    SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from

  19. Nitrate assimilation gene cluster from the heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120.

    Science.gov (United States)

    Frías, J E; Flores, E; Herrero, A

    1997-01-01

    A region of the genome of the filamentous, nitrogen-fixing, heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 that contains a cluster of genes involved in nitrate assimilation has been identified. The genes nir, encoding nitrite reductase, and nrtABC, encoding elements of a nitrate permease, have been cloned. Insertion of a gene cassette into the nir-nrtA region impaired expression of narB, the nitrate reductase structural gene which together with nrtD is found downstream from nrtC in the gene cluster. This indicates that the nir-nrtABCD-narB genes are cotranscribed, thus constituting an operon. Expression of the nir operon in strain PCC 7120 is subjected to ammonium-promoted repression and takes place from an NtcA-activated promoter located 460 bp upstream from the start of the nir gene. In the absence of ammonium, cellular levels of the products of the nir operon are higher in the presence of nitrate than in the absence of combined nitrogen.

  20. 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

    2011-09-01

    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.

  1. Developmental expression and gene/enzyme identifications in the alpha esterase gene cluster of Drosophila melanogaster.

    Science.gov (United States)

    Campbell, P M; de Q Robin, G C; Court, L N; Dorrian, S J; Russell, R J; Oakeshott, J G

    2003-10-01

    Here we show how the 10 genes of the alpha esterase cluster of Drosophila melanogaster have diverged substantially in their expression profiles. Together with previously described sequence divergence this suggests substantial functional diversification. By peptide mass fingerprinting and in vitro gene expression we have also shown that two of the genes encode the isozymes EST9 (formerly ESTC) and EST23. EST9 is the major 'alpha staining' esterase in zymograms of gut tissues in feeding stages while orthologues of EST23 confer resistance to organophosphorus insecticides in other higher Diptera. The results for EST9 and EST23 concur with previous suggestions that the products of the alpha esterase cluster function in digestion and detoxification of xenobiotic esters. However, many of the other genes in the cluster show developmental or tissue-specific expression that seems inconsistent with such roles. Furthermore, there is generally poor correspondence between the mRNA expression patterns of the remaining eight genes and isozymes previously characterized by standard techniques of electrophoresis and staining, suggesting that the alpha cluster might only account for a small minority of the esterase isozyme profile.

  2. Structure and gene cluster of the O-antigen of Escherichia coli O133.

    Science.gov (United States)

    Shashkov, Alexander S; Zhang, Yuanyuan; Sun, Qiangzheng; Guo, Xi; Senchenkova, Sof'ya N; Perepelov, Andrei V; Knirel, Yuriy A

    2016-07-22

    The O-specific polysaccharide (O-antigen) of Escherichia coli O133 was obtained by mild acid hydrolysis of the lipopolysaccharide of E. coli O133. The structure of the hexasaccharide repeating unit of the polysaccharide was elucidated by (1)H and (13)C NMR spectroscopy, including a two-dimensional (1)H-(1)H ROESY experiment: Functions of genes in the O-antigen gene cluster were putatively identified by comparison with sequences in the available databases and, particularly, an encoded predicted multifunctional glycosyltransferase was assigned to three α-l-rhamnosidic linkages.

  3. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  4. Clusters of Factors Identify A High Prevalence of Pregnancy Involvement Among US Adolescent Males.

    Science.gov (United States)

    Lau, May; Lin, Hua; Flores, Glenn

    2015-08-01

    The study purpose was to use recursive partitioning analysis (RPA) to identify factors that, when clustered, are associated with a high prevalence of pregnancy involvement among US adolescent males. The National Survey of Family Growth is a nationally representative survey of individuals 15-44 years old. RPA was done for the 2002 and 2006-2010 cycles to identify factors which, when combined, identify adolescent males with the highest prevalence of pregnancy involvement. Pregnancy-involvement prevalence among adolescent males was 6 %. Two clusters of adolescent males have the highest pregnancy-involvement prevalence, at 84-87 %. In RPA, the highest pregnancy-involvement prevalence (87 %) was seen in adolescent males who ever HIV tested, had >4 lifetime sexual partners, reported less than an almost certain chance of feeling less physical pleasure with condom use, had an educational attainment of 4 lifetime sexual partners, reported less than an almost certain chance of feeling less physical pleasure with condom use, had an educational attainment ≥11th grade, were >17 years old, and had their first contraceptive education ≥10th grade, had a pregnancy-involvement prevalence of 84 %. Pregnancy-prevention efforts among adolescent males who have been involved in a pregnancy may need to target risk factors identified in clusters with the highest pregnancy prevalence to prevent subsequent pregnancies in these adolescent males and improve their future outcomes.

  5. Identifying candidate driver genes by integrative ovarian cancer genomics data

    Science.gov (United States)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  6. A whole genome RNAi screen identifies replication stress response genes.

    Science.gov (United States)

    Kavanaugh, Gina; Ye, Fei; Mohni, Kareem N; Luzwick, Jessica W; Glick, Gloria; Cortez, David

    2015-11-01

    Proper DNA replication is critical to maintain genome stability. When the DNA replication machinery encounters obstacles to replication, replication forks stall and the replication stress response is activated. This response includes activation of cell cycle checkpoints, stabilization of the replication fork, and DNA damage repair and tolerance mechanisms. Defects in the replication stress response can result in alterations to the DNA sequence causing changes in protein function and expression, ultimately leading to disease states such as cancer. To identify additional genes that control the replication stress response, we performed a three-parameter, high content, whole genome siRNA screen measuring DNA replication before and after a challenge with replication stress as well as a marker of checkpoint kinase signalling. We identified over 200 replication stress response genes and subsequently analyzed how they influence cellular viability in response to replication stress. These data will serve as a useful resource for understanding the replication stress response.

  7. A conserved cluster of three PRD-class homeobox genes (homeobrain, rx and orthopedia in the Cnidaria and Protostomia

    Directory of Open Access Journals (Sweden)

    Mazza Maureen E

    2010-07-01

    Full Text Available Abstract Background Homeobox genes are a superclass of transcription factors with diverse developmental regulatory functions, which are found in plants, fungi and animals. In animals, several Antennapedia (ANTP-class homeobox genes reside in extremely ancient gene clusters (for example, the Hox, ParaHox, and NKL clusters and the evolution of these clusters has been implicated in the morphological diversification of animal bodyplans. By contrast, similarly ancient gene clusters have not been reported among the other classes of homeobox genes (that is, the LIM, POU, PRD and SIX classes. Results Using a combination of in silico queries and phylogenetic analyses, we found that a cluster of three PRD-class homeobox genes (Homeobrain (hbn, Rax (rx and Orthopedia (otp is present in cnidarians, insects and mollusks (a partial cluster comprising hbn and rx is present in the placozoan Trichoplax adhaerens. We failed to identify this 'HRO' cluster in deuterostomes; in fact, the Homeobrain gene appears to be missing from the chordate genomes we examined, although it is present in hemichordates and echinoderms. To illuminate the ancestral organization and function of this ancient cluster, we mapped the constituent genes against the assembled genome of a model cnidarian, the sea anemone Nematostella vectensis, and characterized their spatiotemporal expression using in situ hybridization. In N. vectensis, these genes reside in a span of 33 kb with the same gene order as previously reported in insects. Comparisons of genomic sequences and expressed sequence tags revealed the presence of alternative transcripts of Nv-otp and two highly unusual protein-coding polymorphisms in the terminal helix of the Nv-rx homeodomain. A population genetic survey revealed the Rx polymorphisms to be widespread in natural populations. During larval development, all three genes are expressed in the ectoderm, in non-overlapping territories along the oral-aboral axis, with distinct

  8. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    Directory of Open Access Journals (Sweden)

    Irina Vyazunova

    Full Text Available Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.

  9. Sleeping Beauty Mouse Models Identify Candidate Genes Involved in Gliomagenesis

    Science.gov (United States)

    Vyazunova, Irina; Maklakova, Vilena I.; Berman, Samuel; De, Ishani; Steffen, Megan D.; Hong, Won; Lincoln, Hayley; Morrissy, A. Sorana; Taylor, Michael D.; Akagi, Keiko; Brennan, Cameron W.; Rodriguez, Fausto J.; Collier, Lara S.

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma. PMID:25423036

  10. Comparative transcriptional profiling of the axolotl limb identifies a tripartite regeneration-specific gene program.

    Directory of Open Access Journals (Sweden)

    Dunja Knapp

    Full Text Available Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression - early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation.

  11. Astronomy and big data a data clustering approach to identifying uncertain galaxy morphology

    CERN Document Server

    Edwards, Kieran Jay

    2014-01-01

    With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as “Uncertain”. This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Select...

  12. Analysis of Pigeon (Columba) Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation.

    Science.gov (United States)

    Wang, Ying; Ding, Jia-Tong; Yang, Hai-Ming; Yan, Zheng-Jie; Cao, Wei; Li, Yang-Bai

    2015-01-01

    Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp) were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species.

  13. Analysis of Pigeon (Columba Ovary Transcriptomes to Identify Genes Involved in Blue Light Regulation.

    Directory of Open Access Journals (Sweden)

    Ying Wang

    Full Text Available Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species.

  14. Evolutionary formation of gene clusters by reorganization: the meleagrin/roquefortine paradigm in different fungi.

    Science.gov (United States)

    Martín, Juan F; Liras, Paloma

    2016-02-01

    The biosynthesis of secondary metabolites in fungi is catalyzed by enzymes encoded by genes linked in clusters that are frequently co-regulated at the transcriptional level. Formation of gene clusters may take place by de novo assembly of genes recruited from other cellular functions, but also novel gene clusters are formed by reorganization of progenitor clusters and are distributed by horizontal gene transfer. This article reviews (i) the published information on the roquefortine/meleagrin/neoxaline gene clusters of Penicillium chrysogenum (Penicillium rubens) and the short roquefortine cluster of Penicillium roqueforti, and (ii) the correlation of the genes present in those clusters with the enzymes and metabolites derived from these pathways. The P. chrysogenum roq/mel cluster consists of seven genes and includes a gene (roqT) encoding a 12-TMS transporter protein of the MFS family. Interestingly, the orthologous P. roquefortine gene cluster has only four genes and the roqT gene is present as a residual pseudogene that encodes only small peptides. Two of the genes present in the central region of the P. chrysogenum roq/mel cluster have been lost during the evolutionary formation of the short cluster and the order of the structural genes in the cluster has been rearranged. The two lost genes encode a N1 atom hydroxylase (nox) and a roquefortine scaffold-reorganizing oxygenase (sro). As a consequence P. roqueforti has lost the ability to convert the roquefortine-type carbon skeleton to the glandicoline/meleagrin-type scaffold and is unable to produce glandicoline B, meleagrin and neoxaline. The loss of this genetic information is not recent and occurred probably millions of years ago when a progenitor Penicillium strain got adapted to life in a few rich habitats such as cheese, fermented cereal grains or silage. P. roqueforti may be considered as a "domesticated" variant of a progenitor common to contemporary P. chrysogenum and related Penicillia.

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Fujita André

    2012-10-01

    Full Text Available Abstract 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.

  17. 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.

  18. 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.

  19. 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

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

    DEFF Research Database (Denmark)

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

    Identification of genes explaining variation in quantitative traits or genetic risk factors of human diseases requires both good phenotypic- and genotypic data, but also efficient statistical methods. Genome-wide association studies may reveal association between phenotypic variation and variation...... at nucleotide level, thus potentially identify genetic variants. However, testing million of polymorphic nucleotide positions requires conservative correction for multiple testing which lowers the probability of finding genes with small to moderate effects. To alleviate this, we apply a gene based association...... approach grouping variants accordingly to gene position, thus lowering the number of statistical tests performed and increasing the probability of identifying genes with small to moderate effects. Using this approach we identify numerous genes associated with different types of stresses in Drosophila...

  1. Clustering Gene Expression Data Based on Predicted Differential Effects of G V Interaction

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

    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 G V (gene by variety)interaction using the adjusted unbiased prediction (AUP) method. The predicted G V 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.

  2. Emergent team roles in organizational meetings: Identifying communication patterns via cluster analysis.

    OpenAIRE

    Lehmann-Willenbrock, N.K.; Beck, S.J.; Kauffeld, S.

    2016-01-01

    Previous team role taxonomies have largely relied on self-report data, focused on functional roles, and described individual predispositions or personality traits. Instead, this study takes a communicative approach and proposes that team roles are produced, shaped, and sustained in communicative behaviors. To identify team roles communicatively, 59 regular organizational meetings were videotaped and analyzed. Cluster analysis revealed five emergent roles: the solution seeker, the problem anal...

  3. In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD

    Science.gov (United States)

    Martínez-Flores, Irma; Pérez-Morales, Deyanira; Sánchez-Pérez, Mishael; Paredes, Claudia C.; Collado-Vides, Julio; Salgado, Heladia; Bustamante, Víctor H.

    2016-01-01

    A wide variety of Salmonella enterica serovars cause intestinal and systemic infections to humans and animals. Salmonella Patogenicity Island 1 (SPI-1) is a chromosomal region containing 39 genes that have crucial virulence roles. The AraC-like transcriptional regulator HilD, encoded in SPI-1, positively controls the expression of the SPI-1 genes, as well as of several other virulence genes located outside SPI-1. In this study, we applied a clustering method to the global gene expression data of S. enterica serovar Typhimurium from the COLOMBOS database; thus genes that show an expression pattern similar to that of SPI-1 genes were selected. This analysis revealed nine novel genes that are co-expressed with SPI-1, which are located in different chromosomal regions. Expression analyses and protein-DNA interaction assays showed regulation by HilD for six of these genes: gtgE, phoH, sinR, SL1263 (lpxR) and SL4247 were regulated directly, whereas SL1896 was regulated indirectly. Interestingly, phoH is an ancestral gene conserved in most of bacteria, whereas the other genes show characteristics of genes acquired by Salmonella. A role in virulence has been previously demonstrated for gtgE, lpxR and sinR. Our results further expand the regulon of HilD and thus identify novel possible Salmonella virulence genes. PMID:27886269

  4. Teaching Gene Technology in an Outreach Lab: Students' Assigned Cognitive Load Clusters and the Clusters' Relationships to Learner Characteristics, Laboratory Variables, and Cognitive Achievement

    Science.gov (United States)

    Scharfenberg, Franz-Josef; Bogner, Franz X.

    2013-02-01

    This study classified students into different cognitive load (CL) groups by means of cluster analysis based on their experienced CL in a gene technology outreach lab which has instructionally been designed with regard to CL theory. The relationships of the identified student CL clusters to learner characteristics, laboratory variables, and cognitive achievement were examined using a pre-post-follow-up design. Participants of our day-long module Genetic Fingerprinting were 409 twelfth-graders. During the module instructional phases (pre-lab, theoretical, experimental, and interpretation phases), we measured the students' mental effort (ME) as an index of CL. By clustering the students' module-phase-specific ME pattern, we found three student CL clusters which were independent of the module instructional phases, labeled as low-level, average-level, and high-level loaded clusters. Additionally, we found two student CL clusters that were each particular to a specific module phase. Their members reported especially high ME invested in one phase each: within the pre-lab phase and within the interpretation phase. Differentiating the clusters, we identified uncertainty tolerance, prior experience in experimentation, epistemic interest, and prior knowledge as relevant learner characteristics. We found relationships to cognitive achievement, but no relationships to the examined laboratory variables. Our results underscore the importance of pre-lab and interpretation phases in hands-on teaching in science education and the need for teachers to pay attention to these phases, both inside and outside of outreach laboratory learning settings.

  5. 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.

  6. 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.

  7. Adaptive evolution of the FADS gene cluster within Africa.

    Directory of Open Access Journals (Sweden)

    Rasika A Mathias

    Full Text Available Long chain polyunsaturated fatty acids (LC-PUFAs are essential for brain structure, development, and function, and adequate dietary quantities of LC-PUFAs are thought to have been necessary for both brain expansion and the increase in brain complexity observed during modern human evolution. Previous studies conducted in largely European populations suggest that humans have limited capacity to synthesize brain LC-PUFAs such as docosahexaenoic acid (DHA from plant-based medium chain (MC PUFAs due to limited desaturase activity. Population-based differences in LC-PUFA levels and their product-to-substrate ratios can, in part, be explained by polymorphisms in the fatty acid desaturase (FADS gene cluster, which have been associated with increased conversion of MC-PUFAs to LC-PUFAs. Here, we show evidence that these high efficiency converter alleles in the FADS gene cluster were likely driven to near fixation in African populations by positive selection ∼85 kya. We hypothesize that selection at FADS variants, which increase LC-PUFA synthesis from plant-based MC-PUFAs, played an important role in allowing African populations obligatorily tethered to marine sources for LC-PUFAs in isolated geographic regions, to rapidly expand throughout the African continent 60-80 kya.

  8. Copy number of pilus gene clusters in Haemophilus influenzae and variation in the hifE pilin gene.

    Science.gov (United States)

    Read, T D; Satola, S W; Opdyke, J A; Farley, M M

    1998-04-01

    Brazilian purpuric fever (BPF)-associated Haemophilus influenzae biogroup aegyptius strain F3031 contains two identical copies of a five gene cluster (hifA to hifE) encoding pili similar to well-characterized Hif fimbriae of H. influenzae type b. HifE, the putative pilus tip adhesin of F3031, shares only 40% amino acid sequence similarity with the same molecule from type b strains, whereas the other four proteins have 75 to 95% identity. To determine whether pilus cluster duplication and the hifE(F3031) allele were special features of BPF-associated bacteria, we analyzed a collection of H. influenzae strains by PCR with hifA- and hifE-specific oligonucleotides, by Southern hybridization with a hifC gene probe, and by nucleotide sequencing. The presence of two pilus clusters was limited to some H. influenzae biogroup aegyptius strains. The hifE(F3031) allele was limited to H. influenzae biogroup aegyptius. Two strains contained one copy of hifE(F3031) and one copy of a variant hifE allele. We determined the nucleotide sequences of four hifE genes from H. influenzae biogroup aegyptius and H. influenzae capsule serotypes a and c. The predicted proteins produced by these genes demonstrated only 35 to 70% identity to the three published HifE proteins from nontypeable H. influenzae, serotype b, and BPF strains. The C-terminal third of the molecules implicated in chaperone binding was the most highly conserved region. Three conserved domains in the otherwise highly variable N-terminal putative receptor-binding region of HifE were similar to conserved portions in the N terminus of Neisseria pilus adhesin PilC. We concluded that two pilus clusters and hifE(F3031) were not specific for BPF-causing H. influenzae, and we also identified portions of HifE possibly involved in binding mammalian cell receptors.

  9. A sequence-based approach to identify reference genes for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Chari Raj

    2010-08-01

    Full Text Available Abstract Background An important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer may not be suitable in another (e.g. breast cancer. Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate. Methods Serial analysis of gene expression (SAGE profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR, and their impact on differential expression analysis of microarray data was evaluated. Results We show that (i conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii reference genes identified for lung cancer do not perform well for other cancer types (breast and brain, (iii reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung

  10. A recursive network approach can identify constitutive regulatory circuits in gene expression data

    Science.gov (United States)

    Blasi, Monica Francesca; Casorelli, Ida; Colosimo, Alfredo; Blasi, Francesco Simone; Bignami, Margherita; Giuliani, Alessandro

    2005-03-01

    The activity of the cell is often coordinated by the organisation of proteins into regulatory circuits that share a common function. Genome-wide expression profiles might contain important information on these circuits. Current approaches for the analysis of gene expression data include clustering the individual expression measurements and relating them to biological functions as well as modelling and simulation of gene regulation processes by additional computer tools. The identification of the regulative programmes from microarray experiments is limited, however, by the intrinsic difficulty of linear methods to detect low-variance signals and by the sensitivity of the different approaches. Here we face the problem of recognising invariant patterns of correlations among gene expression reminiscent of regulation circuits. We demonstrate that a recursive neural network approach can identify genetic regulation circuits from expression data for ribosomal and genome stability genes. The proposed method, by greatly enhancing the sensitivity of microarray studies, allows the identification of important aspects of genetic regulation networks and might be useful for the discrimination of the different players involved in regulation circuits. Our results suggest that the constitutive regulatory networks involved in the generic organisation of the cell display a high degree of clustering depending on a modular architecture.

  11. Beta-globin gene cluster haplotypes in Venezuelan sickle cell patients from the State of Aragua

    OpenAIRE

    Nancy Moreno; Martínez, José A.; Zorella Blanco; Leidys Osorio; Patrick Hackshaw

    2002-01-01

    Seven polymorphic sites in the beta-globin gene cluster were analyzed on a sample of 96 chromosomes of Venezuelan sickle cell patients from the State of Aragua. The Benin haplotype was predominant with a frequency of 0.479, followed by the Bantu haplotype (0.406); a minority of cases with other haplotypes was also identified: atypical Bantu A2 (0.042), Senegal (0.031), atypical Bantu A7 (0.021) and Saudi Arabia/Indian (0.021) haplotypes; however, the Cameroon haplotype was not identified in t...

  12. Strategies to identify long noncoding RNAs involved in gene regulation

    Directory of Open Access Journals (Sweden)

    Lee Catherine

    2012-11-01

    Full Text Available Abstract Long noncoding RNAs (lncRNAs have been detected in nearly every cell type and found to be fundamentally involved in many biological processes. The characterization of lncRNAs has immense potential to advance our comprehensive understanding of cellular processes and gene regulation, along with implications for the treatment of human disease. The recent ENCODE (Encyclopedia of DNA Elements study reported 9,640 lncRNA loci in the human genome, which corresponds to around half the number of protein-coding genes. Because of this sheer number and their functional diversity, it is crucial to identify a pool of potentially relevant lncRNAs early on in a given study. In this review, we evaluate the methods for isolating lncRNAs by immunoprecipitation and review the advantages, disadvantages, and applications of three widely used approaches – microarray, tiling array, and RNA-seq – for identifying lncRNAs involved in gene regulation. We also look at ways in which data from publicly available databases such as ENCODE can support the study of lncRNAs.

  13. 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.

  14. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

    Science.gov (United States)

    Jiang, Bing; Li, Shuwen; Jiang, Zhi

    2017-01-01

    Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding. PMID:28232943

  15. Application of Multi-SOM clustering approach to macrophage gene expression analysis.

    Science.gov (United States)

    Ghouila, Amel; Yahia, Sadok Ben; Malouche, Dhafer; Jmel, Haifa; Laouini, Dhafer; Guerfali, Fatma Z; Abdelhak, Sonia

    2009-05-01

    The production of increasingly reliable and accessible gene expression data has stimulated the development of computational tools to interpret such data and to organize them efficiently. The clustering techniques are largely recognized as useful exploratory tools for gene expression data analysis. Genes that show similar expression patterns over a wide range of experimental conditions can be clustered together. This relies on the hypothesis that genes that belong to the same cluster are coregulated and involved in related functions. Nevertheless, clustering algorithms still show limits, particularly for the estimation of the number of clusters and the interpretation of hierarchical dendrogram, which may significantly influence the outputs of the analysis process. We propose here a multi level SOM based clustering algorithm named Multi-SOM. Through the use of clustering validity indices, Multi-SOM overcomes the problem of the estimation of clusters number. To test the validity of the proposed clustering algorithm, we first tested it on supervised training data sets. Results were evaluated by computing the number of misclassified samples. We have then used Multi-SOM for the analysis of macrophage gene expression data generated in vitro from the same individual blood infected with 5 different pathogens. This analysis led to the identification of sets of tightly coregulated genes across different pathogens. Gene Ontology tools were then used to estimate the biological significance of the clustering, which showed that the obtained clusters are coherent and biologically significant.

  16. Identified Circadian Rhythm Genes of Ciliary Epithelium with Differential Display

    Institute of Scientific and Technical Information of China (English)

    Yanxia Li; Dongcheng Lu; Jian Ge; Yanna Li; Yehong Zhuo; Sears ML

    2001-01-01

    Purpose:To identify differential genes expressed in the rabbit ciliary epithelium duringthe circadian cycle of aqueous flow.Methods: Total RNA from ciliary epithelium of rabbits at 8AM (light on 1 hour) and8PM(light off 1 hour) were compared by differential display reverse transcription-polymerase chain reaetion(DD RT-PCR), using 6 % denaturing polyacrylamide electro-phoresis, choose differential display bands, cut and reamplify with the same primer, cloneand sequence. Search the database of Genbank, prolong them with 5' RACE and 3'RACE technique then clone, sequence and search database of Genbank.Results: 93 Significant differences gene expression were detected between light on andlight off in the rabbit ciliary epithelium.Conclusion: Differential display is a powerful tool to screen differentially expressedgenes in circadian rhythm of ciliary epithelium.

  17. Gene-network analysis identifies susceptibility genes related to glycobiology in autism.

    Directory of Open Access Journals (Sweden)

    Bert van der Zwaag

    Full Text Available The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD, and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD.

  18. Identifying genes that mediate anthracyline toxicity in immune cells

    Directory of Open Access Journals (Sweden)

    Amber eFrick

    2015-04-01

    Full Text Available The role of the immune system in response to chemotherapeutic agents remains elusive. The interpatient variability observed in immune and chemotherapeutic cytotoxic responses is likely, at least in part, due to complex genetic differences. Through the use of a panel of genetically diverse mouse inbred strains, we developed a drug screening platform aimed at identifying genes underlying these chemotherapeutic cytotoxic effects on immune cells. Using genome-wide association studies (GWAS, we identified four genome-wide significant quantitative trait loci (QTL that contributed to the sensitivity of doxorubicin and idarubicin in immune cells. Of particular interest, a locus on chromosome 16 was significantly associated with cell viability following idarubicin administration (p = 5.01x10-8. Within this QTL lies App, which encodes amyloid beta precursor protein. Comparison of dose-response curves verified that T-cells in App knockout mice were more sensitive to idarubicin than those of C57BL/6J control mice (p < 0.05.In conclusion, the cellular screening approach coupled with GWAS led to the identification and subsequent validation of a gene involved in T-cell viability after idarubicin treatment. Previous studies have suggested a role for App in in vitro and in vivo cytotoxicity to anticancer agents; the overexpression of App enhances resistance, while the knockdown of this gene is deleterious to cell viability. Thus, further investigations should include performing mechanistic studies, validating additional genes from the GWAS, including Ppfia1 and Ppfibp1, and ultimately translating the findings to in vivo and human studies.

  19. Unusual Gene Order and Organization of the Sea Urchin Hox Cluster

    OpenAIRE

    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, Kevin J.; Hood, Leroy

    2005-01-01

    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...

  20. Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites.

    Science.gov (United States)

    Qin, Zhaohui S; McCue, Lee Ann; Thompson, William; Mayerhofer, Linda; Lawrence, Charles E; Liu, Jun S

    2003-04-01

    The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are key steps toward understanding transcription regulation. In addition to effective laboratory assays, various computational approaches for the detection of TFBS in promoter regions of coexpressed genes have been developed. The availability of complete genome sequences combined with the likelihood that transcription factors and their cognate sites are often conserved during evolution has led to the development of phylogenetic footprinting. The modus operandi of this technique is to search for conserved motifs upstream of orthologous genes from closely related species. The method can identify hundreds of TFBS without prior knowledge of co-regulation or coexpression. Because many of these predicted sites are likely to be bound by the same transcription factor, motifs with similar patterns can be put into clusters so as to infer the sets of co-regulated genes, that is, the regulons. This strategy utilizes only genome sequence information and is complementary to and confirmative of gene expression data generated by microarray experiments. However, the limited data available to characterize individual binding patterns, the variation in motif alignment, motif width, and base conservation, and the lack of knowledge of the number and sizes of regulons make this inference problem difficult. We have developed a Gibbs sampling-based Bayesian motif clustering (BMC) algorithm to address these challenges. Tests on simulated data sets show that BMC produces many fewer errors than hierarchical and K-means clustering methods. The application of BMC to hundreds of predicted gamma-proteobacterial motifs correctly identified many experimentally reported regulons, inferred the existence of previously unreported members of these regulons, and suggested novel regulons.

  1. Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings

    DEFF Research Database (Denmark)

    Jensen, Rikke Krüger; Jensen, Tue S; Kjaer, Per

    2013-01-01

    Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have little...... association with treatment effects in clinical populations, and mostly a weak association with the presence of pain in the general population.However, almost all research into these associations is based on the examination of individual MRI findings, despite its being very common for multiple MRI findings...... to coexist. Therefore, this proof-of-concept study investigated the capacity of a multivariable statistical method to identify clusters of MRI findings and for those clusters to be grouped into pathways of vertebral degeneration....

  2. A hybrid distance measure for clustering expressed sequence tags originating from the same gene family.

    Directory of Open Access Journals (Sweden)

    Keng-Hoong Ng

    Full Text Available BACKGROUND: Clustering is a key step in the processing of Expressed Sequence Tags (ESTs. The primary goal of clustering is to put ESTs from the same transcript of a single gene into a unique cluster. Recent EST clustering algorithms mostly adopt the alignment-free distance measures, where they tend to yield acceptable clustering accuracies with reasonable computational time. Despite the fact that these clustering methods work satisfactorily on a majority of the EST datasets, they have a common weakness. They are prone to deliver unsatisfactory clustering results when dealing with ESTs from the genes derived from the same family. The root cause is the distance measures applied on them are not sensitive enough to separate these closely related genes. METHODOLOGY/PRINCIPAL FINDINGS: We propose a hybrid distance measure that combines the global and local features extracted from ESTs, with the aim to address the clustering problem faced by ESTs derived from the same gene family. The clustering process is implemented using the DBSCAN algorithm. We test the hybrid distance measure on the ten EST datasets, and the clustering results are compared with the two alignment-free EST clustering tools, i.e. wcd and PEACE. The clustering results indicate that the proposed hybrid distance measure performs relatively better (in terms of clustering accuracy than both EST clustering tools. CONCLUSIONS/SIGNIFICANCE: The clustering results provide support for the effectiveness of the proposed hybrid distance measure in solving the clustering problem for ESTs that originate from the same gene family. The improvement of clustering accuracies on the experimental datasets has supported the claim that the sensitivity of the hybrid distance measure is sufficient to solve the clustering problem.

  3. Regulator of complement activation (RCA) gene cluster in Xenopus tropicalis.

    Science.gov (United States)

    Oshiumi, Hiroyuki; Suzuki, Yuzuru; Matsumoto, Misako; Seya, Tsukasa

    2009-05-01

    Genome and expressed sequence tag information of Xenopus tropicalis suggested that short-consensus repeat (SCR)-containing proteins are encoded by three genes that are mapped within a 300-kb downstream of PFKFB2, which is a marker gene for the regulator of complement activation (RCA) loci in human and chicken. Based on this observation, we cloned the three cDNAs of these proteins using 3'- or 5'-RACE technique. Since their primary structures and locations of the proximity to the PFKFB2 locus, we named them amphibian RCA protein (ARC) 1, 2, and 3. Expression in human HEK293 or CHO cells suggested that ARC1 is a soluble protein of Mr approximately 67 kDa, ARC2 is a membrane protein with Mr 44 kDa, and ARC3 a secretary protein with a putative transmembrane region. They were N-glycosylated during maturation. In human and chicken RCA clusters, the order in which genes for soluble, GPI-anchored, and membrane forms of SCR proteins are arranged is from the distant to proximity to the PFKFB2 gene. However, the amphibian ARC1, 2, and 3 resembled one another and did not reflect the same order found in human and chicken RCA genes. This may be due to self-duplication of ARCs to form a family, and it evolved after the amphibia separated from the ancestor of the amniotes, which possessed soluble, GPI-anchored, and membrane forms of SCR protein members. Taken together, frog possesses a RCA locus, but the constitution of the ARC proteins differs from that of the amniotes with a unique self-resemblance.

  4. Analysis of multiple transcriptomes of the African oil palm (Elaeis guineensis) to identify reference genes for RT-qPCR.

    Science.gov (United States)

    Xia, Wei; Mason, Annaliese S; Xiao, Yong; Liu, Zheng; Yang, Yaodong; Lei, Xintao; Wu, Xiaoming; Ma, Zilong; Peng, Ming

    2014-08-20

    The African oil palm (Elaeis guineensis), which is grown in tropical and subtropical regions, is a highly productive oil-bearing crop. For gene expression-based analyses such as reverse transcription-quantitative real time PCR (RT-qPCR), reference genes are essential to provide a baseline with which to quantify relative gene expression. Normalization using reliable reference genes is critical in correctly interpreting expression data from RT-qPCR. In order to identify suitable reference genes in African oil palm, 17 transcriptomes of different tissues obtained from NCBI were systematically assessed for gene expression variation. In total, 53 putative candidate reference genes with coefficient of variation values <3.0 were identified: 18 in reproductive tissue and 35 in vegetative tissue. Analysis for enriched functions showed that approximately 90% of identified genes were clustered in cell component gene functions, and 12 out of 53 genes were traditional housekeeping genes. We selected and validated 16 reference genes chosen from leaf tissue transcriptomes by using RT-qPCR in sets of cold, drought and high salinity treated samples, and ranked expression stability using statistical algorithms geNorm, Normfinder and Bestkeeper. Genes encoding actin, adenine phosphoribosyltransferase and eukaryotic initiation factor 4A genes were the most stable genes over the cold, drought and high salinity stresses. Identification of stably expressed genes as reference gene candidates from multiple transcriptome datasets was found to be reliable and efficient, and some traditional housekeeping genes were more stably expressed than others. We provide a useful molecular genetic resource for future gene expression studies in African oil palm, facilitating molecular genetics approaches for crop improvement in this species. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Back to the sea twice: identifying candidate plant genes for molecular evolution to marine life

    Directory of Open Access Journals (Sweden)

    Reusch Thorsten BH

    2011-01-01

    Full Text Available Abstract Background Seagrasses are a polyphyletic group of monocotyledonous angiosperms that have adapted to a completely submerged lifestyle in marine waters. Here, we exploit two collections of expressed sequence tags (ESTs of two wide-spread and ecologically important seagrass species, the Mediterranean seagrass Posidonia oceanica (L. Delile and the eelgrass Zostera marina L., which have independently evolved from aquatic ancestors. This replicated, yet independent evolutionary history facilitates the identification of traits that may have evolved in parallel and are possible instrumental candidates for adaptation to a marine habitat. Results In our study, we provide the first quantitative perspective on molecular adaptations in two seagrass species. By constructing orthologous gene clusters shared between two seagrasses (Z. marina and P. oceanica and eight distantly related terrestrial angiosperm species, 51 genes could be identified with detection of positive selection along the seagrass branches of the phylogenetic tree. Characterization of these positively selected genes using KEGG pathways and the Gene Ontology uncovered that these genes are mostly involved in translation, metabolism, and photosynthesis. Conclusions These results provide first insights into which seagrass genes have diverged from their terrestrial counterparts via an initial aquatic stage characteristic of the order and to the derived fully-marine stage characteristic of seagrasses. We discuss how adaptive changes in these processes may have contributed to the evolution towards an aquatic and marine existence.

  6. Comparisons of Graph-structure Clustering Methods for Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Zhuo FANG; Lei LIU; Jiong YANG; Qing-Ming LUO; Yi-Xue LI

    2006-01-01

    Although many numerical clustering algorithms have been applied to gene expression data analysis, the essential step is still biological interpretation by manual inspection. The correlation between genetic co-regulation and affiliation to a common biological process is what biologists expect. Here, we introduce some clustering algorithms that are based on graph structure constituted by biological knowledge. After applying a widely used dataset, we compared the result clusters of two of these algorithms in terms of the homogeneity of clusters and coherence of annotation and matching ratio. The results show that the clusters of knowledge-guided analysis are the kernel parts of the clusters of Gene Ontology (GO)-Cluster software, which contains the genes that are most expression correlative and most consistent with biological functions. Moreover, knowledge-guided analysis seems much more applicable than GO-Cluster in a larger dataset.

  7. 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.

  8. Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

    Science.gov (United States)

    Liu, L L; Liu, M J; Ma, M

    2015-09-28

    The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

  9. Identifying redundant and missing relations in the gene ontology.

    Science.gov (United States)

    Mougin, Fleur

    2015-01-01

    Significant efforts have been undertaken for providing the Gene Ontology (GO) in a computable format as well as for enriching it with logical definitions. Automated approaches can thus be applied to GO for assisting its maintenance and for checking its internal coherence. However, inconsistencies may still remain within GO. In this frame, the objective of this work was to audit GO relationships. First, reasoning over relationships was exploited for detecting redundant relations existing between GO concepts. Missing necessary and sufficient conditions were then identified based on the compositional structure of the preferred names of GO concepts. More than one thousand redundant relations and 500 missing necessary and sufficient conditions were found. The proposed approach was thus successful for detecting inconsistencies within GO relations. The application of lexical approaches as well as the exploitation of synonyms and textual definitions could be useful for identifying additional necessary and sufficient conditions. Multiple necessary and sufficient conditions for a given GO concept may be indicative of inconsistencies.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Selections of data preprocessing methods and similarity metrics for gene cluster analysis

    Institute of Scientific and Technical Information of China (English)

    YANG Chunmei; WAN Baikun; GAO Xiaofeng

    2006-01-01

    Clustering is one of the major exploratory techniques for gene expression data analysis. Only with suitable similarity metrics and when datasets are properly preprocessed, can results of high quality be obtained in cluster analysis. In this study, gene expression datasets with external evaluation criteria were preprocessed as normalization by line, normalization by column or logarithm transformation by base-2, and were subsequently clustered by hierarchical clustering, k-means clustering and self-organizing maps (SOMs) with Pearson correlation coefficient or Euclidean distance as similarity metric. Finally, the quality of clusters was evaluated by adjusted Rand index. The results illustrate that k-means clustering and SOMs have distinct advantages over hierarchical clustering in gene clustering, and SOMs are a bit better than k-means when randomly initialized. It also shows that hierarchical clustering prefers Pearson correlation coefficient as similarity metric and dataset normalized by line. Meanwhile, k-means clustering and SOMs can produce better clusters with Euclidean distance and logarithm transformed datasets. These results will afford valuable reference to the implementation of gene expression cluster analysis.

  12. 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

  13. Identifying the genes of unconventional high temperature superconductors.

    Science.gov (United States)

    Hu, Jiangping

    We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d-orbitals of cations that participate in strong in-plane couplings to the p-orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.

  14. Enzymology of aminoglycoside biosynthesis-deduction from gene clusters.

    Science.gov (United States)

    Wehmeier, Udo F; Piepersberg, Wolfgang

    2009-01-01

    The classical aminoglycosides are, with very few exceptions, typically actinobacterial secondary metabolites with antimicrobial activities all mediated by inhibiting translation on the 30S subunit of the bacterial ribosome. Some chemically related natural products inhibit glucosidases by mimicking oligo-alpha-1,4-glucosides. The biochemistry of the aminoglycoside biosynthetic pathways is still a developing field since none of the pathways has been analyzed to completeness as yet. In this chapter we treat the enzymology of aminoglycoside biosyntheses as far as it becomes apparent from recent investigations based on the availability of DNA sequence data of biosynthetic gene clusters for all major structural classes of these bacterial metabolites. We give a more general overview of the field, including descriptions of some key enzymes in various aminoglycoside pathways, whereas in Chapter 20 provides a detailed account of the better-studied enzymology thus far known for the neomycin and butirosin pathways.

  15. Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

    Directory of Open Access Journals (Sweden)

    Megan C. McDonald

    2016-04-01

    Full Text Available Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene.

  16. An Integrated Approach Identifies Nhlh1 and Insm1 as Sonic Hedgehog-regulated Genes in Developing Cerebellum and Medulloblastoma

    Directory of Open Access Journals (Sweden)

    Enrico De Smaele

    2008-01-01

    Full Text Available Medulloblastoma (MB is the most common malignant brain tumor of childhood arising from deregulated cerebellar development. Sonic Hedgehog (Shh pathway plays a critical role in cerebellar development and its aberrant expression has been identified in MB. Gene expression profiling of cerebella from 1- to 14-day-old mice unveiled a cluster of genes whose expression correlates with the levels of Hedgehog (HH activity. From this cluster, we identified Insm1 and Nhlh1/NSCL1 as novel HH targets induced by Shh treatment in cultured cerebellar granule cell progenitors. Nhlh1 promoter was found to be bound and activated by Gli1 transcription factor. Remarkably, the expression of these genes is also upregulated in mouse and human HH-dependent MBs, suggesting that they may be either a part of the HH-induced tumorigenic process or a specific trait of HH-dependent tumor cells.

  17. TF-Cluster: A pipeline for identifying functionally coordinated transcription factors via network decomposition of the shared coexpression connectivity matrix (SCCM

    Directory of Open Access Journals (Sweden)

    Thomson James A

    2011-04-01

    Full Text Available Abstract Background Identifying the key transcription factors (TFs controlling a biological process is the first step toward a better understanding of underpinning regulatory mechanisms. However, due to the involvement of a large number of genes and complex interactions in gene regulatory networks, identifying TFs involved in a biological process remains particularly difficult. The challenges include: (1 Most eukaryotic genomes encode thousands of TFs, which are organized in gene families of various sizes and in many cases with poor sequence conservation, making it difficult to recognize TFs for a biological process; (2 Transcription usually involves several hundred genes that generate a combination of intrinsic noise from upstream signaling networks and lead to fluctuations in transcription; (3 A TF can function in different cell types or developmental stages. Currently, the methods available for identifying TFs involved in biological processes are still very scarce, and the development of novel, more powerful methods is desperately needed. Results We developed a computational pipeline called TF-Cluster for identifying functionally coordinated TFs in two steps: (1 Construction of a shared coexpression connectivity matrix (SCCM, in which each entry represents the number of shared coexpressed genes between two TFs. This sparse and symmetric matrix embodies a new concept of coexpression networks in which genes are associated in the context of other shared coexpressed genes; (2 Decomposition of the SCCM using a novel heuristic algorithm termed "Triple-Link", which searches the highest connectivity in the SCCM, and then uses two connected TF as a primer for growing a TF cluster with a number of linking criteria. We applied TF-Cluster to microarray data from human stem cells and Arabidopsis roots, and then demonstrated that many of the resulting TF clusters contain functionally coordinated TFs that, based on existing literature, accurately represent

  18. A WDR Gene Is a Conserved Member of a Chitin Synthase Gene Cluster and Influences the Cell Wall in Aspergillus nidulans

    Directory of Open Access Journals (Sweden)

    Gea Guerriero

    2016-06-01

    Full Text Available WD40 repeat (WDR proteins are pleiotropic molecular hubs. We identify a WDR gene that is a conserved genomic neighbor of a chitin synthase gene in Ascomycetes. The WDR gene is unique to fungi and plants, and was called Fungal Plant WD (FPWD. FPWD is within a cell wall metabolism gene cluster in the Ascomycetes (Pezizomycotina comprising chsD, a Chs activator and a GH17 glucanase. The FPWD, AN1556.2 locus was deleted in Aspergillus nidulans strain SAA.111 by gene replacement and only heterokaryon transformants were obtained. The re-annotation of Aspergilli genomes shows that AN1556.2 consists of two tightly linked separate genes, i.e., the WDR gene and a putative beta-flanking gene of unknown function. The WDR and the beta-flanking genes are conserved genomic neighbors localized within a recently identified metabolic cell wall gene cluster in genomes of Aspergilli. The heterokaryons displayed increased susceptibility to drugs affecting the cell wall, and their phenotypes, observed by optical, confocal, scanning electron and atomic force microscopy, suggest cell wall alterations. Quantitative real-time PCR shows altered expression of some cell wall-related genes. The possible implications on cell wall biosynthesis are discussed.

  19. Identifying sexual differentiation genes that affect Drosophila life span

    Directory of Open Access Journals (Sweden)

    Tower John

    2009-12-01

    Full Text Available Abstract Background Sexual differentiation often has significant effects on life span and aging phenotypes. For example, males and females of several species have different life spans, and genetic and environmental manipulations that affect life span often have different magnitude of effect in males versus females. Moreover, the presence of a differentiated germ-line has been shown to affect life span in several species, including Drosophila and C. elegans. Methods Experiments were conducted to determine how alterations in sexual differentiation gene activity might affect the life span of Drosophila melanogaster. Drosophila females heterozygous for the tudor[1] mutation produce normal offspring, while their homozygous sisters produce offspring that lack a germ line. To identify additional sexual differentiation genes that might affect life span, the conditional transgenic system Geneswitch was employed, whereby feeding adult flies or developing larvae the drug RU486 causes the over-expression of selected UAS-transgenes. Results In this study germ-line ablation caused by the maternal tudor[1] mutation was examined in a long-lived genetic background, and was found to increase life span in males but not in females, consistent with previous reports. Fitting the data to a Gompertz-Makeham model indicated that the maternal tudor[1] mutation increases the life span of male progeny by decreasing age-independent mortality. The Geneswitch system was used to screen through several UAS-type and EP-type P element mutations in genes that regulate sexual differentiation, to determine if additional sex-specific effects on life span would be obtained. Conditional over-expression of transformer female isoform (traF during development produced male adults with inhibited sexual differentiation, however this caused no significant change in life span. Over-expression of doublesex female isoform (dsxF during development was lethal to males, and produced a limited

  20. Identifying nearby field T dwarfs in the UKIDSS Galactic Clusters Survey

    CERN Document Server

    Lodieu, N; Hambly, N C; Pinfield, D J

    2008-01-01

    We present the discovery of two new late-T dwarfs identified in the UKIRT Infrared Deep Sky Survey (UKIDSS) Galactic Clusters Survey (GCS) Data Release 2 (DR2). These T dwarfs are nearby old T dwarfs along the line of sight to star-forming regions and open clusters targeted by the UKIDSS GCS. They are found towards the Alpha Per cluster and Orion complex, respectively, from a search in 54 square degrees surveyed in five filters. Photometric candidates were picked up in two-colour diagrams, in a very similar manner to candidates extracted from the UKIDSS Large Area Survey (LAS) but taking advantage of the Z filter employed by the GCS. Both candidates exhibit near-infrared J-band spectra with strong methane and water absorption bands characteristic of late-T dwarfs. We derive spectral types of T6.5+/-0.5 and T7+/-1 and estimate photometric distances less than 50 pc for UGCS J030013.86+490142.5 and UGCS J053022.52-052447.4, respectively. The space density of T dwarfs found in the GCS seems consistent with discov...

  1. Genetic diversity within Clostridium botulinum serotypes, botulinum neurotoxin gene clusters and toxin subtypes.

    Science.gov (United States)

    Hill, Karen K; Smith, Theresa J

    2013-01-01

    Clostridium botulinum is a species of spore-forming anaerobic bacteria defined by the expression of any one or two of seven serologically distinct botulinum neurotoxins (BoNTs) designated BoNT/A-G. This Gram-positive bacterium was first identified in 1897 and since then the paralyzing and lethal effects of its toxin have resulted in the recognition of different forms of the intoxication known as food-borne, infant, or wound botulism. Early microbiological and biochemical characterization of C. botulinum isolates revealed that the bacteria within the species had different characteristics and expressed different toxin types. To organize the variable bacterial traits within the species, Group I-IV designations were created. Interestingly, it was observed that isolates within different Groups could express the same toxin type and conversely a single Group could express different toxin types. This discordant phylogeny between the toxin and the host bacteria indicated that horizontal gene transfer of the toxin was responsible for the variation observed within the species. The recent availability of multiple C. botulinum genomic sequences has offered the ability to bioinformatically analyze the locations of the bont genes, the composition of their toxin gene clusters, and the genes flanking these regions to understand their variation. Comparison of the genomic sequences representing multiple serotypes indicates that the bont genes are not in random locations. Instead the analyses revealed specific regions where the toxin genes occur within the genomes representing serotype A, B, C, E, and F C. botulinum strains and C. butyricum type E strains. The genomic analyses have provided evidence of horizontal gene transfer, site-specific insertion, and recombination events. These events have contributed to the variation observed among the neurotoxins, the toxin gene clusters and the bacteria that contain them, and has supported the historical microbiological, and biochemical

  2. Wide Distribution of Foxicin Biosynthetic Gene Clusters in Streptomyces Strains - An Unusual Secondary Metabolite with Various Properties.

    Science.gov (United States)

    Greule, Anja; Marolt, Marija; Deubel, Denise; Peintner, Iris; Zhang, Songya; Jessen-Trefzer, Claudia; De Ford, Christian; Burschel, Sabrina; Li, Shu-Ming; Friedrich, Thorsten; Merfort, Irmgard; Lüdeke, Steffen; Bisel, Philippe; Müller, Michael; Paululat, Thomas; Bechthold, Andreas

    2017-01-01

    Streptomyces diastatochromogenes Tü6028 is known to produce the polyketide antibiotic polyketomycin. The deletion of the pokOIV oxygenase gene led to a non-polyketomycin-producing mutant. Instead, novel compounds were produced by the mutant, which have not been detected before in the wild type strain. Four different compounds were identified and named foxicins A-D. Foxicin A was isolated and its structure was elucidated as an unusual nitrogen-containing quinone derivative using various spectroscopic methods. Through genome mining, the foxicin biosynthetic gene cluster was identified in the draft genome sequence of S. diastatochromogenes. The cluster spans 57 kb and encodes three PKS type I modules, one NRPS module and 41 additional enzymes. A foxBII gene-inactivated mutant of S. diastatochromogenes Tü6028 ΔpokOIV is unable to produce foxicins. Homologous fox biosynthetic gene clusters were found in more than 20 additional Streptomyces strains, overall in about 2.6% of all sequenced Streptomyces genomes. However, the production of foxicin-like compounds in these strains has never been described indicating that the clusters are expressed at a very low level or are silent under fermentation conditions. Foxicin A acts as a siderophore through interacting with ferric ions. Furthermore, it is a weak inhibitor of the Escherichia coli aerobic respiratory chain and shows moderate antibiotic activity. The wide distribution of the cluster and the various properties of the compound indicate a major role of foxicins in Streptomyces strains.

  3. Wide Distribution of Foxicin Biosynthetic Gene Clusters in Streptomyces Strains – An Unusual Secondary Metabolite with Various Properties

    Science.gov (United States)

    Greule, Anja; Marolt, Marija; Deubel, Denise; Peintner, Iris; Zhang, Songya; Jessen-Trefzer, Claudia; De Ford, Christian; Burschel, Sabrina; Li, Shu-Ming; Friedrich, Thorsten; Merfort, Irmgard; Lüdeke, Steffen; Bisel, Philippe; Müller, Michael; Paululat, Thomas; Bechthold, Andreas

    2017-01-01

    Streptomyces diastatochromogenes Tü6028 is known to produce the polyketide antibiotic polyketomycin. The deletion of the pokOIV oxygenase gene led to a non-polyketomycin-producing mutant. Instead, novel compounds were produced by the mutant, which have not been detected before in the wild type strain. Four different compounds were identified and named foxicins A–D. Foxicin A was isolated and its structure was elucidated as an unusual nitrogen-containing quinone derivative using various spectroscopic methods. Through genome mining, the foxicin biosynthetic gene cluster was identified in the draft genome sequence of S. diastatochromogenes. The cluster spans 57 kb and encodes three PKS type I modules, one NRPS module and 41 additional enzymes. A foxBII gene-inactivated mutant of S. diastatochromogenes Tü6028 ΔpokOIV is unable to produce foxicins. Homologous fox biosynthetic gene clusters were found in more than 20 additional Streptomyces strains, overall in about 2.6% of all sequenced Streptomyces genomes. However, the production of foxicin-like compounds in these strains has never been described indicating that the clusters are expressed at a very low level or are silent under fermentation conditions. Foxicin A acts as a siderophore through interacting with ferric ions. Furthermore, it is a weak inhibitor of the Escherichia coli aerobic respiratory chain and shows moderate antibiotic activity. The wide distribution of the cluster and the various properties of the compound indicate a major role of foxicins in Streptomyces strains. PMID:28270798

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

    DEFF Research Database (Denmark)

    Ryge, J.; Winther, Ole; Wienecke, J.;

    2010-01-01

    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...... 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......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...

  5. Blood pressure loci identified with a gene-centric array.

    Science.gov (United States)

    Johnson, Toby; Gaunt, Tom R; Newhouse, Stephen J; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, Richard W; Tzoulaki, Ioanna; O'Brien, Eoin T; Poulter, Neil R; Sever, Peter; Shields, Denis C; Thom, Simon; Wannamethee, Sasiwarang G; Whincup, Peter H; Brown, Morris J; Connell, John M; Dobson, Richard J; Howard, Philip J; Mein, Charles A; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Davey Smith, George; Day, Ian N M; Lawlor, Debbie A; Goodall, Alison H; Fowkes, F Gerald; Abecasis, Gonçalo R; Elliott, Paul; Gateva, Vesela; Braund, Peter S; Burton, Paul R; Nelson, Christopher P; Tobin, Martin D; van der Harst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, Jan A; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-François; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sõber, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, Dag S; Hastie, Claire E; Hedner, Thomas; Lee, Wai K; Melander, Olle; Wahlstrand, Björn; Hardy, Rebecca; Wong, Andrew; Cooper, Jackie A; Palmen, Jutta; Chen, Li; Stewart, Alexandre F R; Wells, George A; Westra, Harm-Jan; Wolfs, Marcel G M; Clarke, Robert; Franzosi, Maria Grazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, John F; Seedorf, Udo; Watkins, Hugh; Ouwehand, Willem H; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, Michael V; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, Philippa J; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, Steve E; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, Alice V; Dominiczak, Anna F; Farrall, Martin; Hingorani, Aroon D; Samani, Nilesh J; Caulfield, Mark J; Munroe, Patricia B

    2011-12-09

    Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

  6. Large-Scale Transposition Mutagenesis of Streptomyces coelicolor Identifies Hundreds of Genes Influencing Antibiotic Biosynthesis.

    Science.gov (United States)

    Xu, Zhong; Wang, Yemin; Chater, Keith F; Ou, Hong-Yu; Xu, H Howard; Deng, Zixin; Tao, Meifeng

    2017-03-15

    Gram-positive Streptomyces bacteria produce thousands of bioactive secondary metabolites, including antibiotics. To systematically investigate genes affecting secondary metabolism, we developed a hyperactive transposase-based Tn5 transposition system and employed it to mutagenize the model species Streptomyces coelicolor, leading to the identification of 51,443 transposition insertions. These insertions were distributed randomly along the chromosome except for some preferred regions associated with relatively low GC content in the chromosomal core. The base composition of the insertion site and its flanking sequences compiled from the 51,443 insertions implied a 19-bp expanded target site surrounding the insertion site, with a slight nucleic acid base preference in some positions, suggesting a relative randomness of Tn5 transposition targeting in the high-GC Streptomyces genome. From the mutagenesis library, 724 mutants involving 365 genes had altered levels of production of the tripyrrole antibiotic undecylprodigiosin (RED), including 17 genes in the RED biosynthetic gene cluster. Genetic complementation revealed that most of the insertions (more than two-thirds) were responsible for the changed antibiotic production. Genes associated with branched-chain amino acid biosynthesis, DNA metabolism, and protein modification affected RED production, and genes involved in signaling, stress, and transcriptional regulation were overrepresented. Some insertions caused dramatic changes in RED production, identifying future targets for strain improvement.IMPORTANCE High-GC Gram-positive streptomycetes and related actinomycetes have provided more than 100 clinical drugs used as antibiotics, immunosuppressants, and antitumor drugs. Their genomes harbor biosynthetic genes for many more unknown compounds with potential as future drugs. Here we developed a useful genome-wide mutagenesis tool based on the transposon Tn5 for the study of secondary metabolism and its regulation

  7. Extended genetic effects of ADH cluster genes on the risk of alcohol dependence: from GWAS to replication.

    Science.gov (United States)

    Park, Byung Lae; Kim, Jee Wook; Cheong, Hyun Sub; Kim, Lyoung Hyo; Lee, Boung Chul; Seo, Cheong Hoon; Kang, Tae-Cheon; Nam, Young-Woo; Kim, Goon-Bo; Shin, Hyoung Doo; Choi, Ihn-Geun

    2013-06-01

    Alcohol dependence (AD) is a multifactorial and polygenic disorder involving complex gene-to-gene and gene-to-environment interactions. Several genome-wide association studies have reported numerous risk factors for AD, but replication results following these studies have been controversial. To identify new candidate genes, the present study used GWAS and replication studies in a Korean cohort with AD. Genome-wide association analysis revealed that two chromosome regions on Chr. 4q22-q23 (ADH gene cluster, including ADH5, ADH4, ADH6, ADH1A, ADH1B, and ADH7) and Chr. 12q24 (ALDH2) showed multiple association signals for the risk of AD. To investigate detailed genetic effects of these ADH genes on AD, a follow-up study of the ADH gene cluster on 4q22-q23 was performed. A total of 90 SNPs, including ADH1B rs1229984 (H47R), were genotyped in an additional 975 Korean subjects. In case-control analysis, ADH1B rs1229984 (H47R) showed the most significant association with the risk of AD (p = 2.63 × 10(-21), OR = 2.35). Moreover, subsequent conditional analyses revealed that all positive associations of other ADH genes in the cluster disappeared, which suggested that ADH1B rs1229984 (H47R) might be the sole functional genetic marker across the ADH gene cluster. Our findings could provide additional information on the ADH gene cluster regarding the risk of AD, as well as a new and important insight into the genetic factors associated with AD.

  8. Apicidin F: characterization and genetic manipulation of a new secondary metabolite gene cluster in the rice pathogen Fusarium fujikuroi.

    Directory of Open Access Journals (Sweden)

    Eva-Maria Niehaus

    Full Text Available The fungus F. fujikuroi is well known for its production of gibberellins causing the 'bakanae' disease of rice. Besides these plant hormones, it is able to produce other secondary metabolites (SMs, such as pigments and mycotoxins. Genome sequencing revealed altogether 45 potential SM gene clusters, most of which are cryptic and silent. In this study we characterize a new non-ribosomal peptide synthetase (NRPS gene cluster that is responsible for the production of the cyclic tetrapeptide apicidin F (APF. This new SM has structural similarities to the known histone deacetylase inhibitor apicidin. To gain insight into the biosynthetic pathway, most of the 11 cluster genes were deleted, and the mutants were analyzed by HPLC-DAD and HPLC-HRMS for their ability to produce APF or new derivatives. Structure elucidation was carried out be HPLC-HRMS and NMR analysis. We identified two new derivatives of APF named apicidin J and K. Furthermore, we studied the regulation of APF biosynthesis and showed that the cluster genes are expressed under conditions of high nitrogen and acidic pH in a manner dependent on the nitrogen regulator AreB, and the pH regulator PacC. In addition, over-expression of the atypical pathway-specific transcription factor (TF-encoding gene APF2 led to elevated expression of the cluster genes under inducing and even repressing conditions and to significantly increased product yields. Bioinformatic analyses allowed the identification of a putative Apf2 DNA-binding ("Api-box" motif in the promoters of the APF genes. Point mutations in this sequence motif caused a drastic decrease of APF production indicating that this motif is essential for activating the cluster genes. Finally, we provide a model of the APF biosynthetic pathway based on chemical identification of derivatives in the cultures of deletion mutants.

  9. 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.

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

    Science.gov (United States)

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

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

  12. FOX gene cluster defects in alveolar capillary dysplasia associated with congenital heart disease.

    Science.gov (United States)

    Laux, Daniela; Malan, Valérie; Bajolle, Fanny; Boudjemline, Younes; Amiel, Jeanne; Bonnet, Damien

    2013-10-01

    The objective was to report two new patients with the diagnosis of alveolar capillary dysplasia and congenital heart disease, to describe the associated cardiac defects seen in these cases and in the literature, and to consider recent genetic advances concerning the FOX transcription factor gene cluster in chromosome 16q24.1q24.2. We retrospectively analysed the records of all patients with congenital heart disease and alveolar capillary dysplasia seen in the Pediatric Cardiology Department between 2005 and 2010. We reviewed all literature published in the English language relating to cases of alveolar capillary dysplasia and congenital heart disease. Two infants with alveolar capillary dysplasia and cardiac malformation were identified: one had an atrioventricular septal defect and a de novo balanced reciprocal translocation t(1;16)(q32;q24), the second infant had a ventricular septal defect. Analysis of 31 cases of the literature including these new cases showed a predominant association of alveolar capillary dysplasia with obstructive left heart disease (35%), as well as an atrioventricular septal defect (29%). FOX gene cluster defects were identified in eight of these patients. Genetic background of alveolar capillary dysplasia is discussed in the light of the balanced reciprocal translocation t(1;16)(q32;q24) identified in the first child of this report. Alveolar capillary dysplasia should be suspected in neonates with congenital heart disease and unexpectedly elevated pulmonary vascular resistances, especially in cases of obstructive left heart disease or atrioventricular septal defect. Detecting FOX gene cluster defects should be considered in infants with alveolar capillary dysplasia with or without congenital heart disease.

  13. 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 ...

  14. 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 ...

  15. Identification and Functional Analysis of the Mycophenolic Acid Gene Cluster of Penicillium roqueforti.

    Directory of Open Access Journals (Sweden)

    Abdiel Del-Cid

    Full Text Available The filamentous fungus Penicillium roqueforti is widely known as the ripening agent of blue-veined cheeses. Additionally, this fungus is able to produce several secondary metabolites, including the meroterpenoid compound mycophenolic acid (MPA. Cheeses ripened with P. roqueforti are usually contaminated with MPA. On the other hand, MPA is a commercially valuable immunosuppressant. However, to date the molecular basis of the production of MPA by P. roqueforti is still unknown. Using a bioinformatic approach, we have identified a genomic region of approximately 24.4 kbp containing a seven-gene cluster that may be involved in the MPA biosynthesis in P. roqueforti. Gene silencing of each of these seven genes (named mpaA, mpaB, mpaC, mpaDE, mpaF, mpaG and mpaH resulted in dramatic reductions in MPA production, confirming that all of these genes are involved in the biosynthesis of the compound. Interestingly, the mpaF gene, originally described in P. brevicompactum as a MPA self-resistance gene, also exerts the same function in P. roqueforti, suggesting that this gene has a dual function in MPA metabolism. The knowledge of the biosynthetic pathway of MPA in P. roqueforti will be important for the future control of MPA contamination in cheeses and the improvement of MPA production for commercial purposes.

  16. 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; Bai, Linquan

    2012-02-01

    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.

  17. Identification and molecular characterization of four new large deletions in the beta-globin gene cluster.

    Science.gov (United States)

    Joly, Philippe; Lacan, Philippe; Garcia, Caroline; Couprie, Nicole; Francina, Alain

    2009-01-01

    Despite the fact that mutations in the human beta-globin gene cluster are essentially point mutations, a significant number of large deletions have also been described. We present here four new large deletions in the beta-globin gene cluster that have been identified on patients displaying an atypical hemoglobin phenotype (high HbF) at routine analysis. The first deletion, which spreads over 2.0 kb, removes the entire beta-globin gene, including its promoter, and is associated with a typical beta-thal minor phenotype. The three other deletions are larger (19.7 to 23.9 kb) and remove both the delta and beta-globin genes. Phenotypically, they look like an HPFH-deletion as they are associated with normal hematological parameters. The precise localization of their 5' and 3' breakpoints gives new insights about the differences between HPFH and (deltabeta)(0)-thalassemia at the molecular level. The importance of detection of these deletions in prenatal diagnosis and newborn screening of hemoglobinopathies is also discussed.

  18. Human paraoxonase gene cluster overexpression alleviates angiotensin II-induced cardiac hypertrophy in mice.

    Science.gov (United States)

    Pei, Jian-Fei; Yan, Yun-Fei; Tang, Xiaoqiang; Zhang, Yang; Cui, Shen-Shen; Zhang, Zhu-Qin; Chen, Hou-Zao; Liu, De-Pei

    2016-11-01

    Cardiac hypertrophy is the strongest predictor of the development of heart failure, and anti-hypertrophic treatment holds the key to improving the clinical syndrome and increasing the survival rates for heart failure. The paraoxonase (PON) gene cluster (PC) protects against atherosclerosis and coronary artery diseases. However, the role of PC in the heart is largely unknown. To evaluate the roles of PC in cardiac hypertrophy, transgenic mice carrying the intact human PON1, PON2, and PON3 genes and their flanking sequences were studied. We demonstrated that the PC transgene (PC-Tg) protected mice from cardiac hypertrophy induced by Ang II; these mice had reduced heart weight/body weight ratios, decreased left ventricular wall thicknesses and increased fractional shortening compared with wild-type (WT) control. The same protective tendency was also observed with an Apoe (-/-) background. Mechanically, PC-Tg normalized the disequilibrium of matrix metalloproteinases (MMPs)/tissue inhibitors of MMPs (TIMPs) in hypertrophic hearts, which might contribute to the protective role of PC-Tg in cardiac fibrosis and, thus, protect against cardiac remodeling. Taken together, our results identify a novel anti-hypertrophic role for the PON gene cluster, suggesting a possible strategy for the treatment of cardiac hypertrophy through elevating the levels of the PON gene family.

  19. Visualizing the software system towards identifying the topic from source code using semantic clustering

    Directory of Open Access Journals (Sweden)

    Kanchan Sharma

    2014-03-01

    Full Text Available In software re-engineering, domain knowledge are valuable source of information for developers. Here, we describe how the coding standards are helpful for the identification of domain while writing the source code. Internal comments and logical identifier names in source code are the key source to find the concept and domain area for the application. One of the Information retrieval techniques, Latent Semantic Indexing (LSI uses this linguistic information such as identifier names and comments in source code to map it with the domain name. Based on the linguistic results from LSI engine, a clustering technique used to group source artifacts that use similar vocabulary and a way of representing complex system into simpler components. It works at the source code textual level and making it language independent. Prior research activity correlated the semantics with structural information and applied it at different level of abstraction. Based on the frequency of the domain terms labeling has been provided after discrete characterization of the clusters, using machine learning and visually explored. Visualization makes the concept detection much easier.

  20. GenCLiP: a software program for clustering gene lists by literature profiling and constructing gene co-occurrence networks related to custom keywords

    Directory of Open Access Journals (Sweden)

    Zhou Yi-Bo

    2008-07-01

    Full Text Available Abstract Background Biomedical researchers often want to explore pathogenesis and pathways regulated by abnormally expressed genes, such as those identified by microarray analyses. Literature mining is an important way to assist in this task. Many literature mining tools are now available. However, few of them allows the user to make manual adjustments to zero in on what he/she wants to know in particular. Results We present our software program, GenCLiP (Gene Cluster with Literature Profiles, which is based on the methods presented by Chaussabel and Sher (Genome Biol 2002, 3(10:RESEARCH0055 that search gene lists to identify functional clusters of genes based on up-to-date literature profiling. Four features were added to this previously described method: the ability to 1 manually curate keywords extracted from the literature, 2 search genes and gene co-occurrence networks related to custom keywords, 3 compare analyzed gene results with negative and positive controls generated by GenCLiP, and 4 calculate probabilities that the resulting genes and gene networks are randomly related. In this paper, we show with a set of differentially expressed genes between keloids and normal control, how implementation of functions in GenCLiP successfully identified keywords related to the pathogenesis of keloids and unknown gene pathways involved in the pathogenesis of keloids. Conclusion With regard to the identification of disease-susceptibility genes, GenCLiP allows one to quickly acquire a primary pathogenesis profile and identify pathways involving abnormally expressed genes not previously associated with the disease.

  1. Fragmentation of an aflatoxin-like gene cluster in a forest pathogen

    Science.gov (United States)

    Secondary metabolic pathway genes are typically clustered in fungi. An exception to this paradigm is seen for genes required for the production of dothistromin, an aflatoxin-like virulence factor produced by the pine needle pathogen Dothistroma septosporum. In contrast to the tight clustering of gen...

  2. 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.

  3. Copy number variants in the kallikrein gene cluster.

    Directory of Open Access Journals (Sweden)

    Pernilla Lindahl

    Full Text Available The kallikrein gene family (KLK1-KLK15 is the largest contiguous group of protease genes within the human genome and is associated with both risk and outcome of cancer and other diseases. We searched for copy number variants in all KLK genes using quantitative PCR analysis and analysis of inheritance patterns of single nucleotide polymorphisms. Two deletions were identified: one 2235-bp deletion in KLK9 present in 1.2% of alleles, and one 3394-bp deletion in KLK15 present in 4.0% of alleles. Each deletion eliminated one complete exon and created out-of-frame coding that eliminated the catalytic triad of the resulting truncated gene product, which therefore likely is a non-functional protein. Deletion breakpoints identified by DNA sequencing located the KLK9 deletion breakpoint to a long interspersed element (LINE repeated sequence, while the deletion in KLK15 is located in a single copy sequence. To search for an association between each deletion and risk of prostate cancer (PC, we analyzed a cohort of 667 biopsied men (266 PC cases and 401 men with no evidence of PC at biopsy using short deletion-specific PCR assays. There was no association between evidence of PC in this cohort and the presence of either gene deletion. Haplotyping revealed a single origin of each deletion, with most recent common ancestor estimates of 3000-8000 and 6000-14 000 years for the deletions in KLK9 and KLK15, respectively. The presence of the deletions on the same haplotypes in 1000 Genomes data of both European and African populations indicate an early origin of both deletions. The old age in combination with homozygous presence of loss-of-function variants suggests that some kallikrein-related peptidases have non-essential functions.

  4. Prediction of heterogeneous differential genes by detecting outliers to a Gaussian tight cluster.

    Science.gov (United States)

    Yang, Zihua; Yang, Zhengrong

    2013-03-05

    Heterogeneously and differentially expressed genes (hDEG) are a common phenomenon due to bio-logical diversity. A hDEG is often observed in gene expression experiments (with two experimental conditions) where it is highly expressed in a few experimental samples, or in drug trial experiments for cancer studies with drug resistance heterogeneity among the disease group. These highly expressed samples are called outliers. Accurate detection of outliers among hDEGs is then desirable for dis- ease diagnosis and effective drug design. The standard approach for detecting hDEGs is to choose the appropriate subset of outliers to represent the experimental group. However, existing methods typically overlook hDEGs with very few outliers. We present in this paper a simple algorithm for detecting hDEGs by sequentially testing for potential outliers with respect to a tight cluster of non- outliers, among an ordered subset of the experimental samples. This avoids making any restrictive assumptions about how the outliers are distributed. We use simulated and real data to illustrate that the proposed algorithm achieves a good separation between the tight cluster of low expressions and the outliers for hDEGs. The proposed algorithm assesses each potential outlier in relation to the cluster of potential outliers without making explicit assumptions about the outlier distribution. Simulated examples and and breast cancer data sets are used to illustrate the suitability of the proposed algorithm for identifying hDEGs with small numbers of outliers.

  5. 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.

  6. Reconstructability analysis as a tool for identifying gene-gene interactions in studies of human diseases.

    Science.gov (United States)

    Shervais, Stephen; Kramer, Patricia L; Westaway, Shawn K; Cox, Nancy J; Zwick, Martin

    2010-01-01

    There are a number of common human diseases for which the genetic component may include an epistatic interaction of multiple genes. Detecting these interactions with standard statistical tools is difficult because there may be an interaction effect, but minimal or no main effect. Reconstructability analysis (RA) uses Shannon's information theory to detect relationships between variables in categorical datasets. We applied RA to simulated data for five different models of gene-gene interaction, and find that even with heritability levels as low as 0.008, and with the inclusion of 50 non-associated genes in the dataset, we can identify the interacting gene pairs with an accuracy of > or =80%. We applied RA to a real dataset of type 2 non-insulin-dependent diabetes (NIDDM) cases and controls, and closely approximated the results of more conventional single SNP disease association studies. In addition, we replicated prior evidence for epistatic interactions between SNPs on chromosomes 2 and 15.

  7. Base J represses genes at the end of polycistronic gene clusters in Leishmania major by promoting RNAP II termination.

    Science.gov (United States)

    Reynolds, David L; Hofmeister, Brigitte T; Cliffe, Laura; Siegel, T Nicolai; Anderson, Britta A; Beverley, Stephen M; Schmitz, Robert J; Sabatini, Robert

    2016-08-01

    The genomes of kinetoplastids are organized into polycistronic gene clusters that are flanked by the modified DNA base J. Previous work has established a role of base J in promoting RNA polymerase II termination in Leishmania spp. where the loss of J leads to termination defects and transcription into adjacent gene clusters. It remains unclear whether these termination defects affect gene expression and whether read through transcription is detrimental to cell growth, thus explaining the essential nature of J. We now demonstrate that reduction of base J at specific sites within polycistronic gene clusters in L. major leads to read through transcription and increased expression of downstream genes in the cluster. Interestingly, subsequent transcription into the opposing polycistronic gene cluster does not lead to downregulation of sense mRNAs. These findings indicate a conserved role for J regulating transcription termination and expression of genes within polycistronic gene clusters in trypanosomatids. In contrast to the expectations often attributed to opposing transcription, the essential nature of J in Leishmania spp. is related to its role in gene repression rather than preventing transcriptional interference resulting from read through and dual strand transcription.

  8. BCIP: a gene-centered platform for identifying potential regulatory genes in breast cancer

    Science.gov (United States)

    Wu, Jiaqi; Hu, Shuofeng; Chen, Yaowen; Li, Zongcheng; Zhang, Jian; Yuan, Hanyu; Shi, Qiang; Shao, Ningsheng; Ying, Xiaomin

    2017-01-01

    Breast cancer is a disease with high heterogeneity. Many issues on tumorigenesis and progression are still elusive. It is critical to identify genes that play important roles in the progression of tumors, especially for tumors with poor prognosis such as basal-like breast cancer and tumors in very young women. To facilitate the identification of potential regulatory or driver genes, we present the Breast Cancer Integrative Platform (BCIP, http://omics.bmi.ac.cn/bcancer/). BCIP maintains multi-omics data selected with strict quality control and processed with uniform normalization methods, including gene expression profiles from 9,005 tumor and 376 normal tissue samples, copy number variation information from 3,035 tumor samples, microRNA-target interactions, co-expressed genes, KEGG pathways, and mammary tissue-specific gene functional networks. This platform provides a user-friendly interface integrating comprehensive and flexible analysis tools on differential gene expression, copy number variation, and survival analysis. The prominent characteristic of BCIP is that users can perform analysis by customizing subgroups with single or combined clinical features, including subtypes, histological grades, pathologic stages, metastasis status, lymph node status, ER/PR/HER2 status, TP53 mutation status, menopause status, age, tumor size, therapy responses, and prognosis. BCIP will help to identify regulatory or driver genes and candidate biomarkers for further research in breast cancer. PMID:28327601

  9. Interferon-α/β receptor-mediated selective induction of a gene cluster by CpG oligodeoxynucleotide 2006

    Directory of Open Access Journals (Sweden)

    Wakiguchi Hiroshi

    2003-07-01

    Full Text Available Abstract Background Oligodeoxynucleotides containing unmethylated CpG motifs (CpG ODN are known to exert a strong adjuvant effect on Th1 immune responses. Although several genes have been reported, no comprehensive study of the gene expression profiles in human cells after stimulation with CpG ODN has been reported. Results This study was designed to identify a CpG-inducible gene cluster that potentially predicts for the molecular mechanisms of clinical efficacy of CpG ODN, by determining mRNA expression in human PBMC after stimulation with CpG ODN. PBMCs were obtained from the peripheral blood of healthy volunteers and cultured in the presence or absence of CpG ODN 2006 for up to 24 hours. The mRNA expression profile was evaluated using a high-density oligonucleotide probe array, GeneChip®. Using hierarchical clustering-analysis, out of a total of 10,000 genes we identified a cluster containing 77 genes as having been up-regulated by CpG ODN. This cluster was further divided into two sub-clusters by means of time-kinetics. (1 Inflammatory cytokines such as IL-6 and GM-CSF were up-regulated predominantly 3 to 6 hours after stimulation with CpG ODN, presumably through activation of a transcription factor, NF-κB. (2 Interferon (IFN-inducible anti-viral proteins, including IFIT1, OAS1 and Mx1, and Th1 chemoattractant IP-10, were up-regulated predominantly 6 to 24 hours after stimulation. Blocking with mAb against IFN-α/β receptor strongly inhibited the induction of these IFN-inducible genes by CpG ODN. Conclusion This study provides new information regarding the possible immunomodulatory effects of CpG ODN in vivo via an IFN-α/β receptor-mediated paracrine pathway.

  10. The human met-ase gene (GZMM): Structure, sequence, and close physical linkage to the serine protease gene cluster on 19p13.3

    Energy Technology Data Exchange (ETDEWEB)

    Pilat, D.; Zimmer, M.; Wekerle, H. [Max-Planck-Institut fuer Psychiatrie, Martinsried (Germany)] [and others

    1994-12-01

    Cosmid clones containing the genes for the human and murine natural killer cell serine protease Met-ase (gene symbol GZMM; granzyme M) were identified by screening human and murine cosmid libraries with rat Met-ase (RNIK-Met-1) cDNA. The human gene has a size of 7.5 kb and an exon-intron structure identical to that of serine protease genes located on human chromosomes 5q11-q12, 14q11.2, and 19p13.3 that are expressed by lymphocytes, mast cells, or myelomonocyte precursors. Using cosmid DNA as a probe for fluorescence in situ hybridization, we identified the chromosomal position of human Met-ase as 19p13.3. Interphase studies with two differentially labeled probes for Met-ase and the azurocidin (AZU1), proteinase 3 (PRTN3), and neutrophil elastase (ELA2) gene cluster revealed that the distance of Met-ase from this gene cluster is in the range of 200 to 500 kb. Using differentially labeled mouse cosmid probes, we also mapped the murine gene for Met-ase to chromosomal band 10C, close to the gene for lamin B2. Thus, the Met-ase, AZU1, PRTN3, and ELA2 genes fall into an established region of homology between mouse chromosomal band 10C and human 19p13.3. 35 refs., 4 figs.

  11. The Epipolythiodiketopiperazine Gene Cluster in Claviceps purpurea: Dysfunctional Cytochrome P450 Enzyme Prevents Formation of the Previously Unknown Clapurines.

    Directory of Open Access Journals (Sweden)

    Julian Dopstadt

    Full Text Available Claviceps purpurea is an important food contaminant and well known for the production of the toxic ergot alkaloids. Apart from that, little is known about its secondary metabolism and not all toxic substances going along with the food contamination with Claviceps are known yet. We explored the metabolite profile of a gene cluster in C. purpurea with a high homology to gene clusters, which are responsible for the formation of epipolythiodiketopiperazine (ETP toxins in other fungi. By overexpressing the transcription factor, we were able to activate the cluster in the standard C. purpurea strain 20.1. Although all necessary genes for the formation of the characteristic disulfide bridge were expressed in the overexpression mutants, the fungus did not produce any ETPs. Isolation of pathway intermediates showed that the common biosynthetic pathway stops after the first steps. Our results demonstrate that hydroxylation of the diketopiperazine backbone is the critical step during the ETP biosynthesis. Due to a dysfunctional enzyme, the fungus is not able to produce toxic ETPs. Instead, the pathway end-products are new unusual metabolites with a unique nitrogen-sulfur bond. By heterologous expression of the Leptosphaeria maculans cytochrome P450 encoding gene sirC, we were able to identify the end-products of the ETP cluster in C. purpurea. The thioclapurines are so far unknown ETPs, which might contribute to the toxicity of other C. purpurea strains with a potentially intact ETP cluster.

  12. The Epipolythiodiketopiperazine Gene Cluster in Claviceps purpurea: Dysfunctional Cytochrome P450 Enzyme Prevents Formation of the Previously Unknown Clapurines

    Science.gov (United States)

    Tudzynski, Paul; Humpf, Hans-Ulrich

    2016-01-01

    Claviceps purpurea is an important food contaminant and well known for the production of the toxic ergot alkaloids. Apart from that, little is known about its secondary metabolism and not all toxic substances going along with the food contamination with Claviceps are known yet. We explored the metabolite profile of a gene cluster in C. purpurea with a high homology to gene clusters, which are responsible for the formation of epipolythiodiketopiperazine (ETP) toxins in other fungi. By overexpressing the transcription factor, we were able to activate the cluster in the standard C. purpurea strain 20.1. Although all necessary genes for the formation of the characteristic disulfide bridge were expressed in the overexpression mutants, the fungus did not produce any ETPs. Isolation of pathway intermediates showed that the common biosynthetic pathway stops after the first steps. Our results demonstrate that hydroxylation of the diketopiperazine backbone is the critical step during the ETP biosynthesis. Due to a dysfunctional enzyme, the fungus is not able to produce toxic ETPs. Instead, the pathway end-products are new unusual metabolites with a unique nitrogen-sulfur bond. By heterologous expression of the Leptosphaeria maculans cytochrome P450 encoding gene sirC, we were able to identify the end-products of the ETP cluster in C. purpurea. The thioclapurines are so far unknown ETPs, which might contribute to the toxicity of other C. purpurea strains with a potentially intact ETP cluster. PMID:27390873

  13. Nonlinear biosynthetic gene cluster dose effect on penicillin production by Penicillium chrysogenum.

    Science.gov (United States)

    Nijland, Jeroen G; Ebbendorf, Bjorg; Woszczynska, Marta; Boer, Rémon; Bovenberg, Roel A L; Driessen, Arnold J M

    2010-11-01

    Industrial penicillin production levels by the filamentous fungus Penicillium chrysogenum increased dramatically by classical strain improvement. High-yielding strains contain multiple copies of the penicillin biosynthetic gene cluster that encodes three key enzymes of the β-lactam biosynthetic pathway. We have analyzed the gene cluster dose effect on penicillin production using the high-yielding P. chrysogenum strain DS17690 that was cured from its native clusters. The amount of penicillin V produced increased with the penicillin biosynthetic gene cluster number but was saturated at high copy numbers. Likewise, transcript levels of the biosynthetic genes pcbAB [δ-(l-α-aminoadipyl)-l-cysteinyl-d-valine synthetase], pcbC (isopenicillin N synthase), and penDE (acyltransferase) correlated with the cluster copy number. Remarkably, the protein level of acyltransferase, which localizes to peroxisomes, was saturated already at low cluster copy numbers. At higher copy numbers, intracellular levels of isopenicillin N increased, suggesting that the acyltransferase reaction presents a limiting step at a high gene dose. Since the number and appearance of the peroxisomes did not change significantly with the gene cluster copy number, we conclude that the acyltransferase activity is limiting for penicillin biosynthesis at high biosynthetic gene cluster copy numbers. These results suggest that at a high penicillin production level, productivity is limited by the peroxisomal acyltransferase import activity and/or the availability of coenzyme A (CoA)-activated side chains.

  14. Identifying genes related to choriogenesis in insect panoistic ovaries by Suppression Subtractive Hybridization

    Directory of Open Access Journals (Sweden)

    Bellés Xavier

    2009-04-01

    Full Text Available Abstract Background Insect ovarioles are classified into two categories: panoistic and meroistic, the later having apparently evolved from an ancestral panoistic type. Molecular data on oogenesis is practically restricted to meroistic ovaries. If we aim at studying the evolutionary transition from panoistic to meroistic, data on panoistic ovaries should be gathered. To this end, we planned the construction of a Suppression Subtractive Hybridization (SSH library to identify genes involved in panoistic choriogenesis, using the cockroach Blattella germanica as model. Results We constructed a post-vitellogenic ovary library by SSH to isolate genes involved in choriogenesis in B. germanica. The tester library was prepared with an ovary pool from 6- to 7-day-old females, whereas the driver library was prepared with an ovary pool from 3- to 4-day-old females. From the SSH library, we obtained 258 high quality sequences which clustered into 34 unique sequences grouped in 19 contigs and 15 singlets. The sequences were compared against non-redundant NCBI databases using BLAST. We found that 44% of the unique sequences had homologous sequences in known genes of other organisms, whereas 56% had no significant similarity to any of the databases entries. A Gene Ontology analysis was carried out, classifying the 34 sequences into different functional categories. Seven of these gene sequences, representative of different categories and processes, were chosen to perform expression studies during the first gonadotrophic cycle by real-time PCR. Results showed that they were mainly expressed during post-vitellogenesis, which validates the SSH technique. In two of them corresponding to novel genes, we demonstrated that they are specifically expressed in the cytoplasm of follicular cells in basal oocytes at the time of choriogenesis. Conclusion The SSH approach has proven to be useful in identifying ovarian genes expressed after vitellogenesis in B. germanica. For

  15. Identification of a gene cluster associated with triclosan catabolism.

    Science.gov (United States)

    Kagle, Jeanne M; Paxson, Clayton; Johnstone, Precious; Hay, Anthony G

    2015-06-01

    Aerobic degradation of bis-aryl ethers like the antimicrobial triclosan typically proceeds through oxygenase-dependent catabolic pathways. Although several studies have reported on bacteria capable of degrading triclosan aerobically, there are no reports describing the genes responsible for this process. In this study, a gene encoding the large subunit of a putative triclosan oxygenase, designated tcsA was identified in a triclosan-degrading fosmid clone from a DNA library of Sphingomonas sp. RD1. Consistent with tcsA's similarity to two-part dioxygenases, a putative FMN-dependent ferredoxin reductase, designated tcsB was found immediately downstream of tcsA. Both tcsAB were found in the midst of a putative chlorocatechol degradation operon. We show that RD1 produces hydroxytriclosan and chlorocatechols during triclosan degradation and that tcsA is induced by triclosan. This is the first study to report on the genetics of triclosan degradation.

  16. Identifying concerted evolution and gene conversion in mammalian gene pairs lasting over 100 million years

    Directory of Open Access Journals (Sweden)

    Scherer Stephen W

    2009-07-01

    Full Text Available Abstract Background Concerted evolution occurs in multigene families and is characterized by stretches of homogeneity and higher sequence similarity between paralogues than between orthologues. Here we identify human gene pairs that have undergone concerted evolution, caused by ongoing gene conversion, since at least the human-mouse divergence. Our strategy involved the identification of duplicated genes with greater similarity within a species than between species. These genes were required to be present in multiple mammalian genomes, suggesting duplication early in mammalian divergence. To eliminate genes that have been conserved due to strong purifying selection, our analysis also required at least one intron to have retained high sequence similarity between paralogues. Results We identified three human gene pairs undergoing concerted evolution (BMP8A/B, DDX19A/B, and TUBG1/2. Phylogenetic investigations reveal that in each case the duplication appears to have occurred prior to eutherian mammalian radiation, with exactly two paralogues present in all examined species. This indicates that all three gene duplication events were established over 100 million years ago. Conclusion The extended duration of concerted evolution in multiple distant lineages suggests that there has been prolonged homogenization of specific segments within these gene pairs. Although we speculate that selection for homogenization could have been utilized in order to maintain crucial homo- or hetero- binding domains, it remains unclear why gene conversion has persisted for such extended periods of time. Through these analyses, our results demonstrate additional examples of a process that plays a definite, although unspecified, role in molecular evolution.

  17. The major resistance gene cluster in lettuce is highly duplicated and spans several megabases.

    Science.gov (United States)

    Meyers, B C; Chin, D B; Shen, K A; Sivaramakrishnan, S; Lavelle, D O; Zhang, Z; Michelmore, R W

    1998-11-01

    At least 10 Dm genes conferring resistance to the oomycete downy mildew fungus Bremia lactucae map to the major resistance cluster in lettuce. We investigated the structure of this cluster in the lettuce cultivar Diana, which contains Dm3. A deletion breakpoint map of the chromosomal region flanking Dm3 was saturated with a variety of molecular markers. Several of these markers are components of a family of resistance gene candidates (RGC2) that encode a nucleotide binding site and a leucine-rich repeat region. These motifs are characteristic of plant disease resistance genes. Bacterial artificial chromosome clones were identified by using duplicated restriction fragment length polymorphism markers from the region, including the nucleotide binding site-encoding region of RGC2. Twenty-two distinct members of the RGC2 family were characterized from the bacterial artificial chromosomes; at least two additional family members exist. The RGC2 family is highly divergent; the nucleotide identity was as low as 53% between the most distantly related copies. These RGC2 genes span at least 3.5 Mb. Eighteen members were mapped on the deletion breakpoint map. A comparison between the phylogenetic and physical relationships of these sequences demonstrated that closely related copies are physically separated from one another and indicated that complex rearrangements have shaped this region. Analysis of low-copy genomic sequences detected no genes, including RGC2, in the Dm3 region, other than sequences related to retrotransposons and transposable elements. The related but divergent family of RGC2 genes may act as a resource for the generation of new resistance phenotypes through infrequent recombination or unequal crossing over.

  18. Whole Genome Analysis of Injectional Anthrax Identifies Two Disease Clusters Spanning More Than 13 Years

    Directory of Open Access Journals (Sweden)

    Paul Keim

    2015-11-01

    Lay Person Interpretation: Injectional anthrax has been plaguing heroin drug users across Europe for more than 10 years. In order to better understand this outbreak, we assessed genomic relationships of all available injectional anthrax strains from four countries spanning a >12 year period. Very few differences were identified using genome-based analysis, but these differentiated the isolates into two distinct clusters. This strongly supports a hypothesis of at least two separate anthrax spore contamination events perhaps during the drug production processes. Identification of two events would not have been possible from standard epidemiological analysis. These comprehensive data will be invaluable for classifying future injectional anthrax isolates and for future geographic attribution.

  19. Prevalence and characteristics of pks genotoxin gene cluster-positive clinical Klebsiella pneumoniae isolates in Taiwan

    Science.gov (United States)

    Chen, Ying-Tsong; Lai, Yi-Chyi; Tan, Mei-Chen; Hsieh, Li-Yun; Wang, Jann-Tay; Shiau, Yih-Ru; Wang, Hui-Ying; Lin, Ann-Chi; Lai, Jui-Fen; Huang, I-Wen; Lauderdale, Tsai-Ling

    2017-01-01

    The pks gene cluster encodes enzymes responsible for the synthesis of colibactin, a genotoxin that has been shown to induce DNA damage and contribute to increased virulence. The present study investigated the prevalence of pks in clinical K. pneumoniae isolates from a national surveillance program in Taiwan, and identified microbiological and molecular factors associated with pks-carriage. The pks gene cluster was detected in 67 (16.7%) of 400 isolates from various specimen types. Multivariate analysis revealed that isolates of K1, K2, K20, and K62 capsular types (p < 0.001), and those more susceptible to antimicrobial agents (p = 0.001) were independent factors strongly associated with pks-carriage. Phylogenetic studies on the sequence type (ST) and pulsed-field gel electrophoresis patterns indicated that the pks-positive isolates belong to a clonal group of ST23 in K1, a locally expanding ST65 clone in K2, a ST268-related K20 group, and a highly clonal ST36:K62 group. Carriage of rmpA, iutC, and ybtA, the genes associated with hypervirulence, was significantly higher in the pks-positive isolates than the pks-negative isolates (95.5% vs. 13.2%, p < 0.001). Further studies to determine the presence of hypervirulent pks-bearing bacterial populations in the flora of community residents and their association with different disease entities may be warranted. PMID:28233784

  20. Characterization of the Biosynthetic Gene Cluster for Benzoxazole Antibiotics A33853 Reveals Unusual Assembly Logic.

    Science.gov (United States)

    Lv, Meinan; Zhao, Junfeng; Deng, Zixin; Yu, Yi

    2015-10-22

    A33853, which shows excellent bioactivity against Leishmania, is a benzoxazole-family compound formed from two moieties of 3-hydroxyanthranilic acid and one 3-hydroxypicolinic acid. In this study, we have identified the gene cluster responsible for the biosynthesis of A33853 in Streptomyces sp. NRRL12068 through genome mining and heterologous expression. Bioinformatics analysis and functional characterization of the orfs contained in the gene cluster revealed that the biosynthesis of A33853 is directed by a group of unusual enzymes. In particular, BomK, annotated as a ketosynthase, was found to catalyze the amide bond formation between 3-hydroxypicolinic and 3-hydroxyanthranilic acid during the assembly of A33853. BomJ, a putative ATP-dependent coenzyme A ligase, and BomN, a putative amidohydrolase, were further proposed to be involved in the benzoxazole formation in A33853 according to gene deletion experiments. Finally, we have successfully utilized mutasynthesis to generate two analogs of A33853, which were reported previously to possess excellent anti-leishmanial activity.

  1. 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 suppo...... 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....

  2. Effects of gene disruptions in the nisin gene cluster of Lactococcus lactis on nisin production and producer immunity

    NARCIS (Netherlands)

    Ra, Runar; Beerthuyzen, Marke M.; Vos, Willem M. de; Saris, Per E.J.; Kuipers, Oscar P.

    1999-01-01

    The lantibiotic nisin is produced by several strains of Lactococcus lactis subsp. lactis. The chromosomally located gene cluster nisABTCIPRKFEG is required for biosynthesis, development of immunity, and regulation of gene expression. In-frame deletions in the nisB and nisT genes, and disruption of

  3. Identifying biological themes within lists of genes with EASE.

    Science.gov (United States)

    Hosack, Douglas A; Dennis, Glynn; Sherman, Brad T; Lane, H Clifford; Lempicki, Richard A

    2003-01-01

    EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE and other high-throughput genomic data. The biological themes returned by EASE recapitulate manually determined themes in previously published gene lists and are robust to varying methods of normalization, intensity calculation and statistical selection of genes. EASE is a powerful tool for rapidly converting the results of functional genomics studies from 'genes' to 'themes'.

  4. Identifying and Tracking Individual Updraft Cores using Cluster Analysis: A TWP-ICE case study

    Science.gov (United States)

    Li, X.; Tao, W.; Collis, S. M.; Varble, A.

    2013-12-01

    Cumulus parameterizations in GCMs depend strongly on the vertical velocity structures of convective updraft cores, or plumes. There hasn't been an accurate way of identifying these cores. The majority of previous studies treat the updraft as a single grid column entity, thus missing many intrinsic characteristics, e.g., the size, strength and spatial orientation of an individual core, its life cycle, and the time variations of the entrainment/detrainment rates associated with its life cycle. In this study, we attempt to apply an innovative algorithm based on the centroid-based k-means cluster analysis to improve our understanding of convection and its associated updraft cores. Both 3-D Doppler radar retrievals and cloud-resolving model simulations of a TWP-ICE campaign case during the monsoon period will be used to test and improve this algorithm. This will provide for more in-depth comparisons between CRM simulations and observations that were not possible previously using the traditional piecewise analysis with each updraft column. The first step is to identify the strongest cores (maximum velocity >10 m/s), since they are well defined and produce definite answers when the cluster analysis algorithm is applied. The preliminary results show that the radar retrieved updraft cores are smaller in size and with the maximum velocity located uniformly at higher levels compared with model simulations. Overall, the model simulations produce much stronger cores compared with the radar retrievals. Within the model simulations, the bulk microphysical scheme simulation produces stronger cores than the spectral bin microphysical scheme. Planned researches include using high temporal-resolution simulations to further track the life cycle of individual updraft cores and study their characteristics.

  5. The urease gene cluster of Vibrio parahaemolyticus does not influence the expression of the thermostable direct hemolysin (TDH) gene or the TDH-related hemolysin gene.

    Science.gov (United States)

    Nakaguchi, Yoshitsugu; Okuda, Jun; Iida, Tetsuya; Nishibuchi, Mitsuaki

    2003-01-01

    In order to investigate why the thermostable direct hemolysin (TDH) and the TDH-related hemolysin (TRH) of Vibrio parahaemolyticus are produced at low levels from urease-positive strains, the effect of the functional urease gene cluster of V. parahaemolyticus on the expression of the tdh and trh genes was examined. Transcriptional lacZ fusions with the tdh1, tdh2, trh1 and trh2 genes representing variants of the tdh and trh genes were integrated into the chromosome of an Escherichia coli strain and a urease-negative V. parahaemolyticus strain. The plasmid-borne urease gene cluster introduced and expressed in these constructs did not affect expression of any of the fusion genes. The amount of TDH produced from a Kanagawa phenomenon-positive V. parahaemolyticus did not change by introduction of the urease gene cluster either. It was concluded therefore that the urease gene cluster is not involved in the regulation of tdh and trh expression.

  6. Gene-trap mutagenesis identifies mammalian genes contributing to intoxication by Clostridium perfringens ε-toxin.

    Directory of Open Access Journals (Sweden)

    Susan E Ivie

    Full Text Available The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1, is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention.

  7. Identifying genes and gene networks involved in chromium metabolism and detoxification in Crambe abyssinica

    Energy Technology Data Exchange (ETDEWEB)

    Zulfiqar, Asma, E-mail: asmazulfiqar08@yahoo.com [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Paulose, Bibin, E-mail: bpaulose@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Chhikara, Sudesh, E-mail: sudesh@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Dhankher, Om Parkash, E-mail: parkash@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States)

    2011-10-15

    Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: > Molecular mechanism of Cr uptake and detoxification in plants is not well known. > We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. > 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. > Pathways linked to stress, ion transport, and sulfur assimilation were affected. > This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.

  8. A gene-trap strategy identifies quiescence-induced genes in synchronized myoblasts

    Indian Academy of Sciences (India)

    Ramkumar Sambasivan; Grace K Pavlath; Jyotsna Dhawan

    2008-03-01

    Cellular quiescence is characterized not only by reduced mitotic and metabolic activity but also by altered gene expression. Growing evidence suggests that quiescence is not merely a basal state but is regulated by active mechanisms. To understand the molecular programme that governs reversible cell cycle exit, we focused on quiescence-related gene expression in a culture model of myogenic cell arrest and activation. Here we report the identification of quiescence-induced genes using a gene-trap strategy. Using a retroviral vector, we generated a library of gene traps in C2C12 myoblasts that were screened for arrest-induced insertions by live cell sorting (FACS-gal). Several independent genetrap lines revealed arrest-dependent induction of gal activity, confirming the efficacy of the FACS screen. The locus of integration was identified in 15 lines. In three lines, insertion occurred in genes previously implicated in the control of quiescence, i.e. EMSY – a BRCA2-interacting protein, p8/com1– a p300HAT-binding protein and MLL5 – a SET domain protein. Our results demonstrate that expression of chromatin modulatory genes is induced in G0, providing support to the notion that this reversibly arrested state is actively regulated.

  9. Soft Topographic Maps for Clustering and Classifying Bacteria Using Housekeeping Genes

    Directory of Open Access Journals (Sweden)

    Massimo La Rosa

    2011-01-01

    Full Text Available The Self-Organizing Map (SOM algorithm is widely used for building topographic maps of data represented in a vectorial space, but it does not operate with dissimilarity data. Soft Topographic Map (STM algorithm is an extension of SOM to arbitrary distance measures, and it creates a map using a set of units, organized in a rectangular lattice, defining data neighbourhood relationships. In the last years, a new standard for identifying bacteria using genotypic information began to be developed. In this new approach, phylogenetic relationships of bacteria could be determined by comparing a stable part of the bacteria genetic code, the so-called “housekeeping genes.” The goal of this work is to build a topographic representation of bacteria clusters, by means of self-organizing maps, starting from genotypic features regarding housekeeping genes.

  10. Two transcription factors, CabA and CabR, are independently involved in multilevel regulation of the biosynthetic gene cluster encoding the novel aminocoumarin, cacibiocin.

    Science.gov (United States)

    Wolański, Marcin; Łebkowski, Tomasz; Kois-Ostrowska, Agnieszka; Zettler, Judith; Apel, Alexander K; Jakimowicz, Dagmara; Zakrzewska-Czerwińska, Jolanta

    2016-04-01

    Aminocoumarins are potent antibiotics belonging to a relatively small group of secondary metabolites produced by actinomycetes. Genome mining of Catenulispora acidiphila has recently led to the discovery of a gene cluster responsible for biosynthesis of novel aminocoumarins, cacibiocins. However, regulation of the expression of this novel gene cluster has not yet been analyzed. In this study, we identify transcriptional regulators of the cacibiocin gene cluster. Using a heterologous expression system, we show that the CabA and CabR proteins encoded by cabA and cabR genes in the cacibiocin gene cluster control the expression of genes involved in the biosynthesis, modification, regulation, and potentially, efflux/resistance of cacibiocins. CabA positively regulates the expression of cabH (the first gene in the cabHIYJKL operon) and cabhal genes encoding key enzymes responsible for the biosynthesis and halogenation of the aminocoumarin moiety, respectively. We provide evidence that CabA is a direct inducer of cacibiocin production, whereas the second transcriptional factor, CabR, is involved in the negative regulation of its own gene and cabT-the latter of which encodes a putative cacibiocin transporter. We also demonstrate that CabR activity is negatively regulated in vitro by aminocoumarin compounds, suggesting the existence of analogous regulation in vivo. Finally, we propose a model of multilevel regulation of gene transcription in the cacibiocin gene cluster by CabA and CabR.

  11. Evolution of C2H2-zinc finger genes and subfamilies in mammals: Species-specific duplication and loss of clusters, genes and effector domains

    Directory of Open Access Journals (Sweden)

    Aubry Muriel

    2008-06-01

    Full Text Available Abstract Background C2H2 zinc finger genes (C2H2-ZNF constitute the largest class of transcription factors in humans and one of the largest gene families in mammals. Often arranged in clusters in the genome, these genes are thought to have undergone a massive expansion in vertebrates, primarily by tandem duplication. However, this view is based on limited datasets restricted to a single chromosome or a specific subset of genes belonging to the large KRAB domain-containing C2H2-ZNF subfamily. Results Here, we present the first comprehensive study of the evolution of the C2H2-ZNF family in mammals. We assembled the complete repertoire of human C2H2-ZNF genes (718 in total, about 70% of which are organized into 81 clusters across all chromosomes. Based on an analysis of their N-terminal effector domains, we identified two new C2H2-ZNF subfamilies encoding genes with a SET or a HOMEO domain. We searched for the syntenic counterparts of the human clusters in other mammals for which complete gene data are available: chimpanzee, mouse, rat and dog. Cross-species comparisons show a large variation in the numbers of C2H2-ZNF genes within homologous mammalian clusters, suggesting differential patterns of evolution. Phylogenetic analysis of selected clusters reveals that the disparity in C2H2-ZNF gene repertoires across mammals not only originates from differential gene duplication but also from gene loss. Further, we discovered variations among orthologs in the number of zinc finger motifs and association of the effector domains, the latter often undergoing sequence degeneration. Combined with phylogenetic studies, physical maps and an analysis of the exon-intron organization of genes from the SCAN and KRAB domains-containing subfamilies, this result suggests that the SCAN subfamily emerged first, followed by the SCAN-KRAB and finally by the KRAB subfamily. Conclusion Our results are in agreement with the "birth and death hypothesis" for the evolution of

  12. Identification of gene clusters associated with host adaptation and antibiotic resistance in Chinese Staphylococcus aureus isolates by microarray-based comparative genomics.

    Directory of Open Access Journals (Sweden)

    Henan Li

    Full Text Available A comparative genomic microarray comprising 2,457 genes from two whole genomes of S. aureus was employed for the comparative genome hybridization analysis of 50 strains of divergent clonal lineages, including methicillin-resistant S. aureus (MRSA, methicillin-susceptible S. aureus (MSSA, and swine strains in China. Large-scale validation was confirmed via polymerase chain reaction in 160 representative clinical strains. All of the 50 strains were clustered into seven different complexes by phylogenetic tree analysis. Thirteen gene clusters were specific to different S. aureus clones. Ten gene clusters, including seven known (vSa3, vSa4, vSaα, vSaβ, Tn5801, and phage ϕSa3 and three novel (C8, C9, and C10 gene clusters, were specific to human MRSA. Notably, two global regulators, sarH2 and sarH3, at cluster C9 were specific to human MRSA, and plasmid pUB110 at cluster C10 was specific to swine MRSA. Three clusters known to be part of SCCmec, vSa4 or Tn5801, and vSaα as well as one novel gene cluster C12 with homology with Tn554 of S. epidermidis were identified as MRSA-specific gene clusters. The replacement of ST239-spa t037 with ST239-spa t030 in Beijing may be a result of its acquisition of vSa4, phage ϕSa1, and ϕSa3. In summary, thirteen critical gene clusters were identified to be contributors to the evolution of host specificity and antibiotic resistance in Chinese S. aureus.

  13. pySAPC, a python package for sparse affinity propagation clustering: Application to odontogenesis whole genome time series gene-expression data.

    Science.gov (United States)

    Cao, Huojun; Amendt, Brad A

    2016-11-01

    Developmental dental anomalies are common forms of congenital defects. The molecular mechanisms of dental anomalies are poorly understood. Systematic approaches such as clustering genes based on similar expression patterns could identify novel genes involved in dental anomalies and provide a framework for understanding molecular regulatory mechanisms of these genes during tooth development (odontogenesis). A python package (pySAPC) of sparse affinity propagation clustering algorithm for large datasets was developed. Whole genome pair-wise similarity was calculated based on expression pattern similarity based on 45 microarrays of several stages during odontogenesis. pySAPC identified 743 gene clusters based on expression pattern similarity during mouse tooth development. Three clusters are significantly enriched for genes associated with dental anomalies (with FDR odontogenesis. Clustering genes based on similar expression profiles recovered several known regulatory relationships for genes involved in odontogenesis, as well as many novel genes that may be involved with the same genetic pathways as genes that have already been shown to contribute to dental defects. By using sparse similarity matrix, pySAPC use much less memory and CPU time compared with the original affinity propagation program that uses a full similarity matrix. This python package will be useful for many applications where dataset(s) are too large to use full similarity matrix. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016. Published by Elsevier B.V.

  14. Clusters of conserved beta cell marker genes for assessment of beta cell phenotype.

    Directory of Open Access Journals (Sweden)

    Geert A Martens

    Full Text Available BACKGROUND AND METHODOLOGY: The aim of this study was to establish a gene expression blueprint of pancreatic beta cells conserved from rodents to humans and to evaluate its applicability to assess shifts in the beta cell differentiated state. Genome-wide mRNA expression profiles of isolated beta cells were compared to those of a large panel of other tissue and cell types, and transcripts with beta cell-abundant and -selective expression were identified. Iteration of this analysis in mouse, rat and human tissues generated a panel of conserved beta cell biomarkers. This panel was then used to compare isolated versus laser capture microdissected beta cells, monitor adaptations of the beta cell phenotype to fasting, and retrieve possible conserved transcriptional regulators. PRINCIPAL FINDINGS: A panel of 332 conserved beta cell biomarker genes was found to discriminate both isolated and laser capture microdissected beta cells from all other examined cell types. Of all conserved beta cell-markers, 15% were strongly beta cell-selective and functionally associated to hormone processing, 15% were shared with neuronal cells and associated to regulated synaptic vesicle transport and 30% with immune plus gut mucosal tissues reflecting active protein synthesis. Fasting specifically down-regulated the latter cluster, but preserved the neuronal and strongly beta cell-selective traits, indicating preserved differentiated state. Analysis of consensus binding site enrichment indicated major roles of CREB/ATF and various nutrient- or redox-regulated transcription factors in maintenance of differentiated beta cell phenotype. CONCLUSIONS: Conserved beta cell marker genes contain major gene clusters defined by their beta cell selectivity or by their additional abundance in either neural cells or in immune plus gut mucosal cells. This panel can be used as a template to identify changes in the differentiated state of beta cells.

  15. Cluster Size Statistic and Cluster Mass Statistic: Two Novel Methods for Identifying Changes in Functional Connectivity Between Groups or Conditions

    Science.gov (United States)

    Ing, Alex; Schwarzbauer, Christian

    2014-01-01

    Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods – the cluster size statistic (CSS) and cluster mass statistic (CMS) – are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity. PMID:24906136

  16. Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

    Science.gov (United States)

    Ing, Alex; Schwarzbauer, Christian

    2014-01-01

    Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

  17. The cylindrospermopsin gene cluster of Aphanizomenon sp. strain 10E6: organization and recombination.

    Science.gov (United States)

    Stüken, Anke; Jakobsen, Kjetill S

    2010-08-01

    Cylindrospermopsin (CYN), a potent hepatoxin, occurs in freshwaters worldwide. Several cyanobacterial species produce the toxin, but the producing species vary between geographical regions. Aphanizomenon flos-aquae, a common algae species in temperate fresh and brackish waters, is one of the three well-documented CYN producers in European waters. So far, no genetic information on the CYN genes of this species has been available. Here, we describe the complete CYN gene cluster, including flanking regions from the German Aphanizomenon sp. strain 10E6 using a full genome sequencing approach by 454 pyrosequencing and bioinformatic identification of the gene cluster. In addition, we have sequenced a approximately 7 kb fragment covering the genes cyrC (partially), cyrA and cyrB (partially) of the same gene cluster in the CYN-producing Aphanizomenon sp. strains 10E9 and 22D11. Comparisons with the orthologous gene clusters of the Australian Cylindrospermopsis raciborskii strains AWT205 and CS505 and the partial gene cluster of the Israeli Aphanizomenon ovalisporum strain ILC-146 revealed a high gene sequence similarity, but also extensive rearrangements of gene order. The high sequence similarity (generally higher than that of 16S rRNA gene fragments from the same strains), atypical GC-content and signs of transposase activities support the suggestion that the CYN genes have been horizontally transferred.

  18. Improvement of gougerotin and nikkomycin production by engineering their biosynthetic gene clusters.

    Science.gov (United States)

    Du, Deyao; Zhu, Yu; Wei, Junhong; Tian, Yuqing; Niu, Guoqing; Tan, Huarong

    2013-07-01

    Nikkomycins and gougerotin are peptidyl nucleoside antibiotics with broad biological activities. The nikkomycin biosynthetic gene cluster comprises one pathway-specific regulatory gene (sanG) and 21 structural genes, whereas the gene cluster for gougerotin biosynthesis includes one putative regulatory gene, one major facilitator superfamily transporter gene, and 13 structural genes. In the present study, we introduced sanG driven by six different promoters into Streptomyces ansochromogenes TH322. Nikkomycin production was increased significantly with the highest increase in engineered strain harboring hrdB promoter-driven sanG. In the meantime, we replaced the native promoter of key structural genes in the gougerotin (gou) gene cluster with the hrdB promoters. The heterologous producer Streptomyces coelicolor M1146 harboring the modified gene cluster produced gougerotin up to 10-fold more than strains carrying the unmodified cluster. Therefore, genetic manipulations of genes involved in antibiotics biosynthesis with the constitutive hrdB promoter present a robust, easy-to-use system generally useful for the improvement of antibiotics production in Streptomyces.

  19. Many nonuniversal archaeal ribosomal proteins are found in conserved gene clusters

    Directory of Open Access Journals (Sweden)

    Jiachen Wang

    2009-01-01

    Full Text Available The genomic associations of the archaeal ribosomal proteins, (r-proteins, were examined in detail. The archaeal versions of the universal r-protein genes are typically in clusters similar or identical and to those found in bacteria. Of the 35 nonuniversal archaeal r-protein genes examined, the gene encoding L18e was found to be associated with the conserved L13 cluster, whereas the genes for S4e, L32e and L19e were found in the archaeal version of the spc operon. Eleven nonuniversal protein genes were not associated with any common genomic context. Of the remaining 19 protein genes, 17 were convincingly assigned to one of 10 previously unrecognized gene clusters. Examination of the gene content of these clusters revealed multiple associations with genes involved in the initiation of protein synthesis, transcription or other cellular processes. The lack of such associations in the universal clusters suggests that initially the ribosome evolved largely independently of other processes. More recently it likely has evolved in concert with other cellular systems. It was also verified that a second copy of the gene encoding L7ae found in some bacteria is actually a homolog of the gene encoding L30e and should be annotated as such.

  20. 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...... Wolbachia. Furthermore, we demonstrated that these operons are transcriptionally active in ovaries and in all other tissues tested, suggesting that T4SS has a significant role in Wolbachia biology. These observations and the identification of homologous vir genes in Wolbachia strains infecting insects...... or nematodes show that vir genes are conserved among Wolbachia strains whatever the phenotype induced by the bacteria....

  1. Sequencing and comparative analysis of fugu protocadherin clusters reveal diversity of protocadherin genes among teleosts

    Directory of Open Access Journals (Sweden)

    Rajasegaran Vikneswari

    2007-03-01

    Full Text Available Abstract Background The synaptic cell adhesion molecules, protocadherins, are a vertebrate innovation that accompanied the emergence of the neural tube and the elaborate central nervous system. In mammals, the protocadherins are encoded by three closely-linked clusters (α, β and γ of tandem genes and are hypothesized to provide a molecular code for specifying the remarkably-diverse neural connections in the central nervous system. Like mammals, the coelacanth, a lobe-finned fish, contains a single protocadherin locus, also arranged into α, β and γ clusters. Zebrafish, however, possesses two protocadherin loci that contain more than twice the number of genes as the coelacanth, but arranged only into α and γ clusters. To gain further insight into the evolutionary history of protocadherin clusters, we have sequenced and analyzed protocadherin clusters from the compact genome of the pufferfish, Fugu rubripes. Results Fugu contains two unlinked protocadherin loci, Pcdh1 and Pcdh2, that collectively consist of at least 77 genes. The fugu Pcdh1 locus has been subject to extensive degeneration, resulting in the complete loss of Pcdh1γ cluster. The fugu Pcdh genes have undergone lineage-specific regional gene conversion processes that have resulted in a remarkable regional sequence homogenization among paralogs in the same subcluster. Phylogenetic analyses show that most protocadherin genes are orthologous between fugu and zebrafish either individually or as paralog groups. Based on the inferred phylogenetic relationships of fugu and zebrafish genes, we have reconstructed the evolutionary history of protocadherin clusters in the teleost fish lineage. Conclusion Our results demonstrate the exceptional evolutionary dynamism of protocadherin genes in vertebrates in general, and in teleost fishes in particular. Besides the 'fish-specific' whole genome duplication, the evolution of protocadherin genes in teleost fishes is influenced by lineage

  2. Sphingolipids regulate telomere clustering by affecting the transcription of genes involved in telomere homeostasis.

    Science.gov (United States)

    Ikeda, Atsuko; Muneoka, Tetsuya; Murakami, Suguru; Hirota, Ayaka; Yabuki, Yukari; Karashima, Takefumi; Nakazono, Kota; Tsuruno, Masahiro; Pichler, Harald; Shirahige, Katsuhiko; Kodama, Yukiko; Shimamoto, Toshi; Mizuta, Keiko; Funato, Kouichi

    2015-07-15

    In eukaryotic organisms, including mammals, nematodes and yeasts, the ends of chromosomes, telomeres are clustered at the nuclear periphery. Telomere clustering is assumed to be functionally important because proper organization of chromosomes is necessary for proper genome function and stability. However, the mechanisms and physiological roles of telomere clustering remain poorly understood. In this study, we demonstrate a role for sphingolipids in telomere clustering in the budding yeast Saccharomyces cerevisiae. Because abnormal sphingolipid metabolism causes downregulation of expression levels of genes involved in telomere organization, sphingolipids appear to control telomere clustering at the transcriptional level. In addition, the data presented here provide evidence that telomere clustering is required to protect chromosome ends from DNA-damage checkpoint signaling. As sphingolipids are found in all eukaryotes, we speculate that sphingolipid-based regulation of telomere clustering and the protective role of telomere clusters in maintaining genome stability might be conserved in eukaryotes.

  3. A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype.

    Science.gov (United States)

    Banelli, Barbara; Brigati, Claudio; Di Vinci, Angela; Casciano, Ida; Forlani, Alessandra; Borzì, Luana; Allemanni, Giorgio; Romani, Massimo

    2012-03-01

    Epigenetic alterations are hallmarks of cancer and powerful biomarkers, whose clinical utilization is made difficult by the absence of standardization and of common methods of data interpretation. The coordinate methylation of many loci in cancer is defined as 'CpG island methylator phenotype' (CIMP) and identifies clinically distinct groups of patients. In neuroblastoma (NB), CIMP is defined by a methylation signature, which includes different loci, but its predictive power on outcome is entirely recapitulated by the PCDHB cluster only. We have developed a robust and cost-effective pyrosequencing-based assay that could facilitate the clinical application of CIMP in NB. This assay permits the unbiased simultaneous amplification and sequencing of 17 out of 19 genes of the PCDHB cluster for quantitative methylation analysis, taking into account all the sequence variations. As some of these variations were at CpG doublets, we bypassed the data interpretation conducted by the methylation analysis software to assign the corrected methylation value at these sites. The final result of the assay is the mean methylation level of 17 gene fragments in the protocadherin B cluster (PCDHB) cluster. We have utilized this assay to compare the methylation levels of the PCDHB cluster between high-risk and very low-risk NB patients, confirming the predictive value of CIMP. Our results demonstrate that the pyrosequencing-based assay herein described is a powerful instrument for the analysis of this gene cluster that may simplify the data comparison between different laboratories and, in perspective, could facilitate its clinical application. Furthermore, our results demonstrate that, in principle, pyrosequencing can be efficiently utilized for the methylation analysis of gene clusters with high internal homologies.

  4. Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

    Science.gov (United States)

    Bae, Yun Jung; Kim, Sung-Eun; Hong, Seong Yeon; Park, Taesun; Lee, Sang Gyu; Choi, Myung-Sook; Sung, Mi-Kyung

    2016-01-01

    Obesity is known to increase the risk of colorectal cancer. However, mechanisms underlying the pathogenesis of obesity-induced colorectal cancer are not completely understood. The purposes of this study were to identify differentially expressed genes in the colon of mice with diet-induced obesity and to select candidate genes as early markers of obesity-associated abnormal cell growth in the colon. C57BL/6N mice were fed normal diet (11% fat energy) or high-fat diet (40% fat energy) and were euthanized at different time points. Genome-wide expression profiles of the colon were determined at 2, 4, 8, and 12 weeks. Cluster analysis was performed using expression data of genes showing log2 fold change of ≥1 or ≤-1 (twofold change), based on time-dependent expression patterns, followed by virtual network analysis. High-fat diet-fed mice showed significant increase in body weight and total visceral fat weight over 12 weeks. Time-course microarray analysis showed that 50, 47, 36, and 411 genes were differentially expressed at 2, 4, 8, and 12 weeks, respectively. Ten cluster profiles representing distinguishable patterns of genes differentially expressed over time were determined. Cluster 4, which consisted of genes showing the most significant alterations in expression in response to high-fat diet over 12 weeks, included Apoa4 (apolipoprotein A-IV), Ppap2b (phosphatidic acid phosphatase type 2B), Cel (carboxyl ester lipase), and Clps (colipase, pancreatic), which interacted strongly with surrounding genes associated with colorectal cancer or obesity. Our data indicate that Apoa4, Ppap2b, Cel, and Clps are candidate early marker genes associated with obesity-related pathological changes in the colon. Genome-wide analyses performed in the present study provide new insights on selecting novel genes that may be associated with the development of diseases of the colon.

  5. Gene network analysis in a pediatric cohort identifies novel lung function genes.

    Directory of Open Access Journals (Sweden)

    Bruce A Ong

    Full Text Available Lung function is a heritable trait and serves as an important clinical predictor of morbidity and mortality for pulmonary conditions in adults, however, despite its importance, no studies have focused on uncovering pediatric-specific loci influencing lung function. To identify novel genetic determinants of pediatric lung function, we conducted a genome-wide association study (GWAS of four pulmonary function traits, including FVC, FEV1, FEV1/FVC and FEF25-75% in 1556 children. Further, we carried out gene network analyses for each trait including all SNPs with a P-value of <1.0 × 10(-3 from the individual GWAS. The GWAS identified SNPs with notable trends towards association with the pulmonary function measures, including the previously described INTS12 locus association with FEV1 (pmeta=1.41 × 10(-7. The gene network analyses identified 34 networks of genes associated with pulmonary function variables in Caucasians. Of those, the glycoprotein gene network reached genome-wide significance for all four variables. P-value range pmeta=6.29 × 10(-4 - 2.80 × 10(-8 on meta-analysis. In this study, we report on specific pathways that are significantly associated with pediatric lung function at genome-wide significance. In addition, we report the first loci associated with lung function in both pediatric Caucasian and African American populations.

  6. Gene-Set Local Hierarchical Clustering (GSLHC--A Gene Set-Based Approach for Characterizing Bioactive Compounds in Terms of Biological Functional Groups.

    Directory of Open Access Journals (Sweden)

    Feng-Hsiang Chung

    Full Text Available Gene-set-based analysis (GSA, which uses the relative importance of functional gene-sets, or molecular signatures, as units for analysis of genome-wide gene expression data, has exhibited major advantages with respect to greater accuracy, robustness, and biological relevance, over individual gene analysis (IGA, which uses log-ratios of individual genes for analysis. Yet IGA remains the dominant mode of analysis of gene expression data. The Connectivity Map (CMap, an extensive database on genomic profiles of effects of drugs and small molecules and widely used for studies related to repurposed drug discovery, has been mostly employed in IGA mode. Here, we constructed a GSA-based version of CMap, Gene-Set Connectivity Map (GSCMap, in which all the genomic profiles in CMap are converted, using gene-sets from the Molecular Signatures Database, to functional profiles. We showed that GSCMap essentially eliminated cell-type dependence, a weakness of CMap in IGA mode, and yielded significantly better performance on sample clustering and drug-target association. As a first application of GSCMap we constructed the platform Gene-Set Local Hierarchical Clustering (GSLHC for discovering insights on coordinated actions of biological functions and facilitating classification of heterogeneous subtypes on drug-driven responses. GSLHC was shown to tightly clustered drugs of known similar properties. We used GSLHC to identify the therapeutic properties and putative targets of 18 compounds of previously unknown characteristics listed in CMap, eight of which suggest anti-cancer activities. The GSLHC website http://cloudr.ncu.edu.tw/gslhc/ contains 1,857 local hierarchical clusters accessible by querying 555 of the 1,309 drugs and small molecules listed in CMap. We expect GSCMap and GSLHC to be widely useful in providing new insights in the biological effect of bioactive compounds, in drug repurposing, and in function-based classification of complex diseases.

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

    Institute of Scientific and Technical Information of China (English)

    Haiyan Pan; Jun Zhu; Danfu Han

    2003-01-01

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

  8. The B-type lamin is required for somatic repression of testis-specific gene clusters

    Science.gov (United States)

    Shevelyov, Y. Y.; Lavrov, S. A.; Mikhaylova, L. M.; Nurminsky, I. D.; Kulathinal, R. J.; Egorova, K. S.; Rozovsky, Y. M.; Nurminsky, D. I.

    2009-01-01

    Large clusters of coexpressed tissue-specific genes are abundant on chromosomes of diverse species. The genes coordinately misexpressed in diverse diseases are also found in similar clusters, suggesting that evolutionarily conserved mechanisms regulate expression of large multigenic regions both in normal development and in its pathological disruptions. Studies on individual loci suggest that silent clusters of coregulated genes are embedded in repressed chromatin domains, often localized to the nuclear periphery. To test this model at the genome-wide scale, we studied transcriptional regulation of large testis-specific gene clusters in somatic tissues of Drosophila. These gene clusters showed a drastic paucity of known expressed transgene insertions, indicating that they indeed are embedded in repressed chromatin. Bioinformatics analysis suggested the major role for the B-type lamin, LamDmo, in repression of large testis-specific gene clusters, showing that in somatic cells as many as three-quarters of these clusters interact with LamDmo. Ablation of LamDmo by using mutants and RNAi led to detachment of testis-specific clusters from nuclear envelope and to their selective transcriptional up-regulation in somatic cells, thus providing the first direct evidence for involvement of the B-type lamin in tissue-specific gene repression. Finally, we found that transcriptional activation of the lamina-bound testis-specific gene cluster in male germ line is coupled with its translocation away from the nuclear envelope. Our studies, which directly link nuclear architecture with coordinated regulation of tissue-specific genes, advance understanding of the mechanisms underlying both normal cell differentiation and developmental disorders caused by lesions in the B-type lamins and interacting proteins. PMID:19218438

  9. De novo assembly of Euphorbia fischeriana root transcriptome identifies prostratin pathway related genes

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    Barrero Roberto A

    2011-12-01

    Full Text Available Abstract Background Euphorbia fischeriana is an important medicinal plant found in Northeast China. The plant roots contain many medicinal compounds including 12-deoxyphorbol-13-acetate, commonly known as prostratin that is a phorbol ester from the tigliane diterpene series. Prostratin is a protein kinase C activator and is effective in the treatment of Human Immunodeficiency Virus (HIV by acting as a latent HIV activator. Latent HIV is currently the biggest limitation for viral eradication. The aim of this study was to sequence, assemble and annotate the E. fischeriana transcriptome to better understand the potential biochemical pathways leading to the synthesis of prostratin and other related diterpene compounds. Results In this study we conducted a high throughput RNA-seq approach to sequence the root transcriptome of E. fischeriana. We assembled 18,180 transcripts, of these the majority encoded protein-coding genes and only 17 transcripts corresponded to known RNA genes. Interestingly, we identified 5,956 protein-coding transcripts with high similarity (> = 75% to Ricinus communis, a close relative to E. fischeriana. We also evaluated the conservation of E. fischeriana genes against EST datasets from the Euphorbeacea family, which included R. communis, Hevea brasiliensis and Euphorbia esula. We identified a core set of 1,145 gene clusters conserved in all four species and 1,487 E. fischeriana paralogous genes. Furthermore, we screened E. fischeriana transcripts against an in-house reference database for genes implicated in the biosynthesis of upstream precursors to prostratin. This identified 24 and 9 candidate transcripts involved in the terpenoid and diterpenoid biosyntehsis pathways, respectively. The majority of the candidate genes in these pathways presented relatively low expression levels except for 1-hydroxy-2-methyl-2-(E-butenyl 4-diphosphate synthase (HDS and isopentenyl diphosphate/dimethylallyl diphosphate synthase (IDS, which

  10. Comparative Transcriptome Analysis Identifies CCDC80 as a Novel Gene Associated with Pulmonary Arterial Hypertension

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    Yuhei eNishimura

    2016-06-01

    Full Text Available Pulmonary arterial hypertension (PAH is a heterogeneous disorder associated with a progressive increase in pulmonary artery resistance and pressure. Although various therapies have been developed, the 5-year survival rate of PAH patients remains low. There is thus an important need to identify novel genes that are commonly dysregulated in PAH of various etiologies and could be used as biomarkers and/or therapeutic targets. In this study, we performed comparative transcriptome analysis of five mammalian PAH datasets downloaded from a public database. We identified 228 differentially expressed genes (DEGs from a rat PAH model caused by inhibition of vascular endothelial growth factor receptor under hypoxic conditions, 379 DEGs from a mouse PAH model associated with systemic sclerosis, 850 DEGs from a mouse PAH model associated with schistosomiasis, 1598 DEGs from one cohort of human PAH patients, and 4260 DEGs from a second cohort of human PAH patients. Gene-by-gene comparison identified four genes that were differentially upregulated or downregulated in parallel in all five sets of DEGs. Expression of coiled-coil domain containing 80 (CCDC80 and anterior gradient 2 genes was significantly increased in the five datasets, whereas expression of SMAD family member 6 and granzyme A was significantly decreased. Weighted gene co-expression network analysis revealed a connection between CCDC80 and collagen type I alpha 1 (COL1A1 expression. To validate the function of CCDC80 in vivo, we knocked out ccdc80 in zebrafish using the clustered regularly interspaced short palindromic repeats (CRISPR/Cas9 system. In vivo imaging of zebrafish expressing a fluorescent protein in endothelial cells showed that ccdc80 deletion significantly increased the diameter of the ventral artery, a vessel supplying blood to the gills. We also demonstrated that expression of col1a1 and endothelin-1 mRNA was significantly decreased in the ccdc80-knockout zebrafish. Finally, we

  11. Identifying novel genes in C. elegans using SAGE tags

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    Chen Nansheng

    2010-12-01

    Full Text Available Abstract Background Despite extensive efforts devoted to predicting protein-coding genes in genome sequences, many bona fide genes have not been found and many existing gene models are not accurate in all sequenced eukaryote genomes. This situation is partly explained by the fact that gene prediction programs have been developed based on our incomplete understanding of gene feature information such as splicing and promoter characteristics. Additionally, full-length cDNAs of many genes and their isoforms are hard to obtain due to their low level or rare expression. In order to obtain full-length sequences of all protein-coding genes, alternative approaches are required. Results In this project, we have developed a method of reconstructing full-length cDNA sequences based on short expressed sequence tags which is called sequence tag-based amplification of cDNA ends (STACE. Expressed tags are used as anchors for retrieving full-length transcripts in two rounds of PCR amplification. We have demonstrated the application of STACE in reconstructing full-length cDNA sequences using expressed tags mined in an array of serial analysis of gene expression (SAGE of C. elegans cDNA libraries. We have successfully applied STACE to recover sequence information for 12 genes, for two of which we found isoforms. STACE was used to successfully recover full-length cDNA sequences for seven of these genes. Conclusions The STACE method can be used to effectively reconstruct full-length cDNA sequences of genes that are under-represented in cDNA sequencing projects and have been missed by existing gene prediction methods, but their existence has been suggested by short sequence tags such as SAGE tags.

  12. Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia.

    Science.gov (United States)

    Lips, E S; Cornelisse, L N; Toonen, R F; Min, J L; Hultman, C M; Holmans, P A; O'Donovan, M C; Purcell, S M; Smit, A B; Verhage, M; Sullivan, P F; Visscher, P M; Posthuma, D

    2012-10-01

    Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia.

  13. Analysis of the retinal gene expression profile after hypoxic preconditioning identifies candidate genes for neuroprotection

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    Wenzel Andreas

    2008-02-01

    Full Text Available Abstract Background Retinal degeneration is a main cause of blindness in humans. Neuroprotective therapies may be used to rescue retinal cells and preserve vision. Hypoxic preconditioning stabilizes the transcription factor HIF-1α in the retina and strongly protects photoreceptors in an animal model of light-induced retinal degeneration. To address the molecular mechanisms of the protection, we analyzed the transcriptome of the hypoxic retina using microarrays and real-time PCR. Results Hypoxic exposure induced a marked alteration in the retinal transcriptome with significantly different expression levels of 431 genes immediately after hypoxic exposure. The normal expression profile was restored within 16 hours of reoxygenation. Among the differentially regulated genes, several candidates for neuroprotection were identified like metallothionein-1 and -2, the HIF-1 target gene adrenomedullin and the gene encoding the antioxidative and cytoprotective enzyme paraoxonase 1 which was previously not known to be a hypoxia responsive gene in the retina. The strongly upregulated cyclin dependent kinase inhibitor p21 was excluded from being essential for neuroprotection. Conclusion Our data suggest that neuroprotection after hypoxic preconditioning is the result of the differential expression of a multitude of genes which may act in concert to protect visual cells against a toxic insult.

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

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    Ye Zhi-Qiang

    2011-08-01

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

  15. Identifying intimate partner violence at entry to prenatal care: clustering routine clinical information.

    Science.gov (United States)

    Anderson, Barbara A; Marshak, Helen Hopp; Hebbeler, Donna L

    2002-01-01

    Intimate partner violence (IPV) is the greatest trauma-related risk to American women. Pregnant women are no exception, and escalation of IPV frequently occurs during pregnancy. Many studies have linked IPV during pregnancy to adverse maternal and fetal outcomes. This study examined IPV at the beginning of prenatal care to identify correlates of routine entry-to-care information with responses on a validated IPV screening tool, the Abuse Assessment Screen. The purpose of the study was to identify specific data from routine, standard intake information, which could alert clinicians to the potential of violence even in the presence of a negative IPV score or no formally administered screening tool. The point prevalence of abuse, as measured by the Abuse Assessment Screen at entry to care, was slightly in excess of the national mean, reinforcing the need for continual assessment throughout pregnancy. Abused women in this study were more likely to be young, single, and without family or partner support. These women relied on friends for support, admitted to depression, and desired their pregnancies. The findings are consistent with previous studies. Further research needs to be conducted to determine if this cluster of findings at entry to care, with or without a positive score on an IPV screening tool, are consistent markers for an increased risk of IPV.

  16. Psychophysiological responses to visceral and somatic pain in functional chest pain identify clinically relevant pain clusters.

    Science.gov (United States)

    Farmer, A D; Coen, S J; Kano, M; Naqvi, H; Paine, P A; Scott, S M; Furlong, P L; Lightman, S L; Knowles, C H; Aziz, Q

    2014-01-01

    Despite chronic pain being a feature of functional chest pain (FCP) its experience is variable. The factors responsible for this variability remain unresolved. We aimed to address these knowledge gaps, hypothesizing that the psychophysiological profiles of FCP patients will be distinct from healthy subjects. 20 Rome III defined FCP patients (nine males, mean age 38.7 years, range 28-59 years) and 20 healthy age-, sex-, and ethnicity-matched controls (nine males, mean 38.2 years, range 24-49) had anxiety, depression, and personality traits measured. Subjects had sympathetic and parasympathetic nervous system parameters measured at baseline and continuously thereafter. Subjects received standardized somatic (nail bed pressure) and visceral (esophageal balloon distension) stimuli to pain tolerance. Venous blood was sampled for cortisol at baseline, post somatic pain and post visceral pain. Patients had higher neuroticism, state and trait anxiety, and depression scores but lower extroversion scores vs controls (all p visceral stimulus (p = 0.009) and had a higher cortisol at baseline, and following pain (all p pain they increased their parasympathetic tone (p ≤ 0.008). The amalgamating the data, we identified two psychophysiologically distinct 'pain clusters'. Patients were overrepresented in the cluster characterized by high neuroticism, trait anxiety, baseline cortisol, pain hypersensitivity, and parasympathetic response to pain (all p < 0.03). In future, such delineations in FCP populations may facilitate individualization of treatment based on psychophysiological profiling. © 2013 John Wiley & Sons Ltd.

  17. Dissection of Two Complex Clusters of Resistance Genes in Lettuce (Lactuca sativa).

    Science.gov (United States)

    Christopoulou, Marilena; McHale, Leah K; Kozik, Alex; Reyes-Chin Wo, Sebastian; Wroblewski, Tadeusz; Michelmore, Richard W

    2015-07-01

    Of the over 50 phenotypic resistance genes mapped in lettuce, 25 colocalize to three major resistance clusters (MRC) on chromosomes 1, 2, and 4. Similarly, the majority of candidate resistance genes encoding nucleotide binding-leucine rich repeat (NLR) proteins genetically colocalize with phenotypic resistance loci. MRC1 and MRC4 span over 66 and 63 Mb containing 84 and 21 NLR-encoding genes, respectively, as well as 765 and 627 genes that are not related to NLR genes. Forward and reverse genetic approaches were applied to dissect MRC1 and MRC4. Transgenic lines exhibiting silencing were selected using silencing of β-glucuronidase as a reporter. Silencing of two of five NLR-encoding gene families resulted in abrogation of nine of 14 tested resistance phenotypes mapping to these two regions. At MRC1, members of the coiled coil-NLR-encoding RGC1 gene family were implicated in host and nonhost resistance through requirement for Dm5/8- and Dm45-mediated resistance to downy mildew caused by Bremia lactucae as well as the hypersensitive response to effectors AvrB, AvrRpm1, and AvrRpt2 of the nonpathogen Pseudomonas syringae. At MRC4, RGC12 family members, which encode toll interleukin receptor-NLR proteins, were implicated in Dm4-, Dm7-, Dm11-, and Dm44-mediated resistance to B. lactucae. Lesions were identified in the sequence of a candidate gene within dm7 loss-of-resistance mutant lines, confirming that RGC12G confers Dm7.

  18. Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

    Science.gov (United States)

    Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

    2009-02-01

    Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

  19. Beta-globin gene cluster haplotypes in Venezuelan sickle cell patients from the State of Aragua

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    Nancy Moreno

    2002-01-01

    Full Text Available Seven polymorphic sites in the beta-globin gene cluster were analyzed on a sample of 96 chromosomes of Venezuelan sickle cell patients from the State of Aragua. The Benin haplotype was predominant with a frequency of 0.479, followed by the Bantu haplotype (0.406; a minority of cases with other haplotypes was also identified: atypical Bantu A2 (0.042, Senegal (0.031, atypical Bantu A7 (0.021 and Saudi Arabia/Indian (0.021 haplotypes; however, the Cameroon haplotype was not identified in this study. Our results are in agreement with the historical records that establish Sudanese and Bantu origins for the African slaves brought into Venezuela.

  20. New natural products isolated from Metarhizium robertsii ARSEF 23 by chemical screening and identification of the gene cluster through engineered biosynthesis in Aspergillus nidulans A1145.

    Science.gov (United States)

    Kato, Hiroki; Tsunematsu, Yuta; Yamamoto, Tsuyoshi; Namiki, Takuya; Kishimoto, Shinji; Noguchi, Hiroshi; Watanabe, Kenji

    2016-07-01

    To rapidly identify novel natural products and their associated biosynthetic genes from underutilized and genetically difficult-to-manipulate microbes, we developed a method that uses (1) chemical screening to isolate novel microbial secondary metabolites, (2) bioinformatic analyses to identify a potential biosynthetic gene cluster and (3) heterologous expression of the genes in a convenient host to confirm the identity of the gene cluster and the proposed biosynthetic mechanism. The chemical screen was achieved by searching known natural product databases with data from liquid chromatographic and high-resolution mass spectrometric analyses collected on the extract from a target microbe culture. Using this method, we were able to isolate two new meroterpenes, subglutinols C (1) and D (2), from an entomopathogenic filamentous fungus Metarhizium robertsii ARSEF 23. Bioinformatics analysis of the genome allowed us to identify a gene cluster likely to be responsible for the formation of subglutinols. Heterologous expression of three genes from the gene cluster encoding a polyketide synthase, a prenyltransferase and a geranylgeranyl pyrophosphate synthase in Aspergillus nidulans A1145 afforded an α-pyrone-fused uncyclized diterpene, the expected intermediate of the subglutinol biosynthesis, thereby confirming the gene cluster to be responsible for the subglutinol biosynthesis. These results indicate the usefulness of our methodology in isolating new natural products and identifying their associated biosynthetic gene cluster from microbes that are not amenable to genetic manipulation. Our method should facilitate the natural product discovery efforts by expediting the identification of new secondary metabolites and their associated biosynthetic genes from a wider source of microbes.

  1. Functional Analysis of Promoters in the Nisin Gene Cluster of Lactococcus lactis

    NARCIS (Netherlands)

    Ruyter, Pascalle G.G.A. de; Kuipers, Oscar P.; Beerthuyzen, Marke M.; Alen-Boerrigter, Ingrid van; Vos, Willem M. de

    1996-01-01

    The promoters in the nisin gene cluster nisABTCIPRKFEG of Lactococcus lactis were characterized by primer extension and transcriptional fusions to the Escherichia coli promoterless β-glucuronidase gene (gusA). Three promoters preceding the nisA, nisR, and nisF genes, which all give rise to gusA expr

  2. 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....

  3. Power training and postmenopausal hormone therapy affect transcriptional control of specific co-regulated gene clusters in skeletal muscle

    Science.gov (United States)

    Fey, Vidal; Törmäkangas, Timo; Ronkainen, Paula H. A.; Taaffe, Dennis R.; Takala, Timo; Koskinen, Satu; Cheng, Sulin; Puolakka, Jukka; Kujala, Urho M.; Suominen, Harri; Sipilä, Sarianna; Kovanen, Vuokko

    2010-01-01

    At the moment, there is no clear molecular explanation for the steeper decline in muscle performance after menopause or the mechanisms of counteractive treatments. The goal of this genome-wide study was to identify the genes and gene clusters through which power training (PT) comprising jumping activities or estrogen containing hormone replacement therapy (HRT) may affect skeletal muscle properties after menopause. We used musculus vastus lateralis samples from early stage postmenopausal (50–57 years old) women participating in a yearlong randomized double-blind placebo-controlled trial with PT and HRT interventions. Using microarray platform with over 24,000 probes, we identified 665 differentially expressed genes. The hierarchical clustering method was used to assort the genes. Additionally, enrichment analysis of gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was carried out to clarify whether assorted gene clusters are enriched with particular functional categories. The analysis revealed transcriptional regulation of 49 GO/KEGG categories. PT upregulated transcription in “response to contraction”—category revealing novel candidate genes for contraction-related regulation of muscle function while HRT upregulated gene expression related to functionality of mitochondria. Moreover, several functional categories tightly related to muscle energy metabolism, development, and function were affected regardless of the treatment. Our results emphasize that during the early stages of the postmenopause, muscle properties are under transcriptional modulation, which both PT and HRT partially counteract leading to preservation of muscle power and potentially reducing the risk for aging-related muscle weakness. More specifically, PT and HRT may function through improving energy metabolism, response to contraction as well as by preserving functionality of the mitochondria. Electronic supplementary material The online version of this

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

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    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. Genomic sequence analysis of the 238-kb swine segment with a cluster of TRIM and olfactory receptor genes located, but with no class I genes, at the distal end of the SLA class I region.

    Science.gov (United States)

    Ando, Asako; Shigenari, Atsuko; Kulski, Jerzy K; Renard, Christine; Chardon, Patrick; Shiina, Takashi; Inoko, Hidetoshi

    2005-12-01

    Continuous genomic sequence has been previously determined for the swine leukocyte antigen (SLA) class I region from the TNF gene cluster at the border between the major histocompatibility complex (MHC) class III and class I regions to the UBD gene at the telomeric end of the classical class I gene cluster (SLA-1 to SLA-5, SLA-9, SLA-11). To complete the genomic sequence of the entire SLA class I genomic region, we have analyzed the genomic sequences of two BAC clones carrying a continuous 237,633-bp-long segment spanning from the TRIM15 gene to the UBD gene located on the telomeric side of the classical SLA class I gene cluster. Fifteen non-class I genes, including the zinc finger and the tripartite motif (TRIM) ring-finger-related family genes and olfactory receptor genes, were identified in the 238-kilobase (kb) segment, and their location in the segment was similar to their apparent human homologs. In contrast, a human segment (alpha block) spanning about 375 kb from the gene ETF1P1 and from the HLA-J to HLA-F genes was absent from the 238-kb swine segment. We conclude that the gene organization of the MHC non-class I genes located in the telomeric side of the classical SLA class I gene cluster is remarkably similar between the swine and the human segments, although the swine lacks a 375-kb segment corresponding to the human alpha block.

  6. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    Science.gov (United States)

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led

  7. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    Directory of Open Access Journals (Sweden)

    Daniel Wuttke

    Full Text Available Dietary restriction (DR, limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/. To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2 had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of

  8. Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

    Science.gov (United States)

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple

  9. Identifying the Interaction between Genes and Gene Products Based on Frequently Seen Verbs in Medline Abstracts.

    Science.gov (United States)

    Sekimizu; Park; Tsujii

    1998-01-01

    We have selected the most frequently seen verbs from raw texts made up of 1-million-words of Medline abstracts, and we were able to identify (or bracket) noun phrases contained in the corpus, with a precision rate of 90%. Then, based on the noun-phrase-bracketted corpus, we tried to find the subject and object terms for some frequently seen verbs in the domain. The precision rate of finding the right subject and object for each verb was about 73%. This task was only made possible because we were able to linguistically analyze (or parse) a large quantity of a raw corpus. Our approach will be useful for classifying genes and gene products and for identifying the interaction between them. It is the first step of our effort in building a genome-related thesaurus and hierarchies in a fully automatic way.

  10. Microarray Expression Data Identify DCC as a Candidate Gene for Early Meningioma Progression.

    Science.gov (United States)

    Schulten, Hans-Juergen; Hussein, Deema; Al-Adwani, Fatima; Karim, Sajjad; Al-Maghrabi, Jaudah; Al-Sharif, Mona; Jamal, Awatif; Al-Ghamdi, Fahad; Baeesa, Saleh S; Bangash, Mohammed; Chaudhary, Adeel; Al-Qahtani, Mohammed

    2016-01-01

    Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (DCC) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into DCC low expression (3 grade I and 3 grade II tumors), DCC medium expression (2 grade I and 1 grade II tumors), and DCC high expression (5 grade I tumors) groups. Comparison between the DCC low expression and DCC high expression groups resulted in 416 DEGs (p-value2). The most significantly downregulated genes in the DCC low expression group comprised DCC, phosphodiesterase 1C (PDE1C), calmodulin-dependent 70kDa olfactomedin 2 (OLFM2), glutathione S-transferase mu 5 (GSTM5), phosphotyrosine interaction domain containing 1 (PID1), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (SEMA6D), and indolethylamine N-methyltransferase (INMT). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (C5orf63), homeodomain interacting protein kinase 2 (HIPK2), and basic helix-loop-helix family, member e40 (BHLHE40). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, DCC may constitute a valid biomarker to

  11. A minimal nitrogen fixation gene cluster from Paenibacillus sp. WLY78 enables expression of active nitrogenase in Escherichia coli.

    Science.gov (United States)

    Wang, Liying; Zhang, Lihong; Liu, Zhanzhi; Liu, Zhangzhi; Zhao, Dehua; Liu, Xiaomeng; Zhang, Bo; Xie, Jianbo; Hong, Yuanyuan; Li, Pengfei; Chen, Sanfeng; Dixon, Ray; Li, Jilun

    2013-01-01

    Most biological nitrogen fixation is catalyzed by molybdenum-dependent nitrogenase, an enzyme complex comprising two component proteins that contains three different metalloclusters. Diazotrophs contain a common core of nitrogen fixation nif genes that encode the structural subunits of the enzyme and components required to synthesize the metalloclusters. However, the complement of nif genes required to enable diazotrophic growth varies significantly amongst nitrogen fixing bacteria and archaea. In this study, we identified a minimal nif gene cluster consisting of nine nif genes in the genome of Paenibacillus sp. WLY78, a gram-positive, facultative anaerobe isolated from the rhizosphere of bamboo. We demonstrate that the nif genes in this organism are organized as an operon comprising nifB, nifH, nifD, nifK, nifE, nifN, nifX, hesA and nifV and that the nif cluster is under the control of a σ(70) (σ(A))-dependent promoter located upstream of nifB. To investigate genetic requirements for diazotrophy, we transferred the Paenibacillus nif cluster to Escherichia coli. The minimal nif gene cluster enables synthesis of catalytically active nitrogenase in this host, when expressed either from the native nifB promoter or from the T7 promoter. Deletion analysis indicates that in addition to the core nif genes, hesA plays an important role in nitrogen fixation and is responsive to the availability of molybdenum. Whereas nif transcription in Paenibacillus is regulated in response to nitrogen availability and by the external oxygen concentration, transcription from the nifB promoter is constitutive in E. coli, indicating that negative regulation of nif transcription is bypassed in the heterologous host. This study demonstrates the potential for engineering nitrogen fixation in a non-nitrogen fixing organism with a minimum set of nine nif genes.

  12. A minimal nitrogen fixation gene cluster from Paenibacillus sp. WLY78 enables expression of active nitrogenase in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Liying Wang

    Full Text Available Most biological nitrogen fixation is catalyzed by molybdenum-dependent nitrogenase, an enzyme complex comprising two component proteins that contains three different metalloclusters. Diazotrophs contain a common core of nitrogen fixation nif genes that encode the structural subunits of the enzyme and components required to synthesize the metalloclusters. However, the complement of nif genes required to enable diazotrophic growth varies significantly amongst nitrogen fixing bacteria and archaea. In this study, we identified a minimal nif gene cluster consisting of nine nif genes in the genome of Paenibacillus sp. WLY78, a gram-positive, facultative anaerobe isolated from the rhizosphere of bamboo. We demonstrate that the nif genes in this organism are organized as an operon comprising nifB, nifH, nifD, nifK, nifE, nifN, nifX, hesA and nifV and that the nif cluster is under the control of a σ(70 (σ(A-dependent promoter located upstream of nifB. To investigate genetic requirements for diazotrophy, we transferred the Paenibacillus nif cluster to Escherichia coli. The minimal nif gene cluster enables synthesis of catalytically active nitrogenase in this host, when expressed either from the native nifB promoter or from the T7 promoter. Deletion analysis indicates that in addition to the core nif genes, hesA plays an important role in nitrogen fixation and is responsive to the availability of molybdenum. Whereas nif transcription in Paenibacillus is regulated in response to nitrogen availability and by the external oxygen concentration, transcription from the nifB promoter is constitutive in E. coli, indicating that negative regulation of nif transcription is bypassed in the heterologous host. This study demonstrates the potential for engineering nitrogen fixation in a non-nitrogen fixing organism with a minimum set of nine nif genes.

  13. A minimal nitrogen fixation gene cluster from Paenibacillus sp. WLY78 enables expression of active nitrogenase in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Liying Wang

    Full Text Available Most biological nitrogen fixation is catalyzed by molybdenum-dependent nitrogenase, an enzyme complex comprising two component proteins that contains three different metalloclusters. Diazotrophs contain a common core of nitrogen fixation nif genes that encode the structural subunits of the enzyme and components required to synthesize the metalloclusters. However, the complement of nif genes required to enable diazotrophic growth varies significantly amongst nitrogen fixing bacteria and archaea. In this study, we identified a minimal nif gene cluster consisting of nine nif genes in the genome of Paenibacillus sp. WLY78, a gram-positive, facultative anaerobe isolated from the rhizosphere of bamboo. We demonstrate that the nif genes in this organism are organized as an operon comprising nifB, nifH, nifD, nifK, nifE, nifN, nifX, hesA and nifV and that the nif cluster is under the control of a σ(70 (σ(A-dependent promoter located upstream of nifB. To investigate genetic requirements for diazotrophy, we transferred the Paenibacillus nif cluster to Escherichia coli. The minimal nif gene cluster enables synthesis of catalytically active nitrogenase in this host, when expressed either from the native nifB promoter or from the T7 promoter. Deletion analysis indicates that in addition to the core nif genes, hesA plays an important role in nitrogen fixation and is responsive to the availability of molybdenum. Whereas nif transcription in Paenibacillus is regulated in response to nitrogen availability and by the external oxygen concentration, transcription from the nifB promoter is constitutive in E. coli, indicating that negative regulation of nif transcription is bypassed in the heterologous host. This study demonstrates the potential for engineering nitrogen fixation in a non-nitrogen fixing organism with a minimum set of nine nif genes.

  14. A Minimal Nitrogen Fixation Gene Cluster from Paenibacillus sp. WLY78 Enables Expression of Active Nitrogenase in Escherichia coli

    Science.gov (United States)

    Zhao, Dehua; Liu, Xiaomeng; Zhang, Bo; Xie, Jianbo; Hong, Yuanyuan; Li, Pengfei; Chen, Sanfeng; Dixon, Ray; Li, Jilun

    2013-01-01

    Most biological nitrogen fixation is catalyzed by molybdenum-dependent nitrogenase, an enzyme complex comprising two component proteins that contains three different metalloclusters. Diazotrophs contain a common core of nitrogen fixation nif genes that encode the structural subunits of the enzyme and components required to synthesize the metalloclusters. However, the complement of nif genes required to enable diazotrophic growth varies significantly amongst nitrogen fixing bacteria and archaea. In this study, we identified a minimal nif gene cluster consisting of nine nif genes in the genome of Paenibacillus sp. WLY78, a gram-positive, facultative anaerobe isolated from the rhizosphere of bamboo. We demonstrate that the nif genes in this organism are organized as an operon comprising nifB, nifH, nifD, nifK, nifE, nifN, nifX, hesA and nifV and that the nif cluster is under the control of a σ70 (σA)-dependent promoter located upstream of nifB. To investigate genetic requirements for diazotrophy, we transferred the Paenibacillus nif cluster to Escherichia coli. The minimal nif gene cluster enables synthesis of catalytically active nitrogenase in this host, when expressed either from the native nifB promoter or from the T7 promoter. Deletion analysis indicates that in addition to the core nif genes, hesA plays an important role in nitrogen fixation and is responsive to the availability of molybdenum. Whereas nif transcription in Paenibacillus is regulated in response to nitrogen availability and by the external oxygen concentration, transcription from the nifB promoter is constitutive in E. coli, indicating that negative regulation of nif transcription is bypassed in the heterologous host. This study demonstrates the potential for engineering nitrogen fixation in a non-nitrogen fixing organism with a minimum set of nine nif genes. PMID:24146630

  15. Bayesian History Reconstruction of Complex Human Gene Clusters on a Phylogeny

    CERN Document Server

    Vinař, Tomáš; Song, Giltae; Siepel, Adam

    2009-01-01

    Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analysis. Improved understanding of these clusters is of utmost importance, since they have been shown to be the source of evolutionary innovation, and have been linked to multiple diseases, including HIV and a variety of cancers. Previously, Zhang et al. (2008) developed an algorithm for reconstructing parsimonious evolutionary histories of such gene clusters, using only human genomic sequence data. In this paper, we propose a probabilistic model for the evolution of gene clusters on a phylogeny, and an MCMC algorithm for reconstruction of duplication histories from genomic sequences in multiple species. Several projects are underway to obtain high quality BAC-based assemblies of duplicated clusters in multiple species, and we anticipate that our method will be useful in analyzing these valuable new data sets.

  16. Epidermal growth factor gene is a newly identified candidate gene for gout

    Science.gov (United States)

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

  17. An elm EST database for identifying leaf beetle egg-induced defense genes

    Directory of Open Access Journals (Sweden)

    Büchel Kerstin

    2012-06-01

    Full Text Available Abstract Background Plants can defend themselves against herbivorous insects prior to the onset of larval feeding by responding to the eggs laid on their leaves. In the European field elm (Ulmus minor, egg laying by the elm leaf beetle ( Xanthogaleruca luteola activates the emission of volatiles that attract specialised egg parasitoids, which in turn kill the eggs. Little is known about the transcriptional changes that insect eggs trigger in plants and how such indirect defense mechanisms are orchestrated in the context of other biological processes. Results Here we present the first large scale study of egg-induced changes in the transcriptional profile of a tree. Five cDNA libraries were generated from leaves of (i untreated control elms, and elms treated with (ii egg laying and feeding by elm leaf beetles, (iii feeding, (iv artificial transfer of egg clutches, and (v methyl jasmonate. A total of 361,196 ESTs expressed sequence tags (ESTs were identified which clustered into 52,823 unique transcripts (Unitrans and were stored in a database with a public web interface. Among the analyzed Unitrans, 73% could be annotated by homology to known genes in the UniProt (Plant database, particularly to those from Vitis, Ricinus, Populus and Arabidopsis. Comparative in silico analysis among the different treatments revealed differences in Gene Ontology term abundances. Defense- and stress-related gene transcripts were present in high abundance in leaves after herbivore egg laying, but transcripts involved in photosynthesis showed decreased abundance. Many pathogen-related genes and genes involved in phytohormone signaling were expressed, indicative of jasmonic acid biosynthesis and activation of jasmonic acid responsive genes. Cross-comparisons between different libraries based on expression profiles allowed the identification of genes with a potential relevance in egg-induced defenses, as well as other biological processes, including signal transduction

  18. 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

  19. An efficient method to identify galaxy clusters by using SuperCOSMOS, 2MASS and WISE data

    Institute of Scientific and Technical Information of China (English)

    XU WeiWei; WEN ZhongLue; HAN JinLin

    2014-01-01

    The survey data of Wide-field Infrared Survey Explorer (WISE) provide an opportunity for the identification of galaxy clusters.We present an efficient method for detecting galaxy clusters by combining the WISE data with SuperCOSMOS and 2MASS data.After performing star-galaxy separation,we calculate the number of companion galaxies around the galaxies with photometric redshifts previously estimated by the SuperCOSMOS,2MASS and WISE data.A scaled richness Rscal ≥ 30 is set as a criterion to identify clusters.From a sky area of 275 deg2 of the Sloan Digital Sky Survey Stripe 82 region,we identify 302 clusters in the redshift range of 0.1 < z < 0.35,247 (82%) of which are previously known SDSS clusters.The results suggest that our method is efficient for identifying galaxy clusters by using the all sky data of the SuperCOSMOS,2MASS and WISE.

  20. Cluster Analysis in the COPDGene Study Identifies Subtypes of Smokers with Distinct Patterns of Airway Disease and Emphysema

    Science.gov (United States)

    Castaldi, Peter J; Dy, Jennifer; Ross, James; Chang, Yale; Washko, George R; Curran-Everett, Douglas; Williams, Andre; Lynch, David A; Make, Barry J; Crapo, James D; Bowler, Russ P; Regan, Elizabeth A; Hokanson, John E; Kinney, Greg L; Han, Meilan K; Soler, Xavier; Ramsdell, Joseph W; Barr, R Graham; Foreman, Marilyn; van Beek, Edwin; Casaburi, Richard; Criner, Gerald J; Lutz, Sharon M; Rennard, Steven I; Santorico, Stephanie; Sciurba, Frank C; DeMeo, Dawn L; Hersh, Craig P; Silverman, Edwin K; Cho, Michael H

    2014-01-01

    Background There is notable heterogeneity in the clinical presentation of patients with COPD. To characterize this heterogeneity, we sought to identify subgroups of smokers by applying cluster analysis to data from the COPDGene Study. Methods We applied a clustering method, k-means, to data from 10,192 smokers in the COPDGene Study. After splitting the sample into a training and validation set, we evaluated three sets of input features across a range of k (user-specified number of clusters). Stable solutions were tested for association with four COPD-related measures and five genetic variants previously associated with COPD at genome-wide significance. The results were confirmed in the validation set. Findings We identified four clusters that can be characterized as 1) relatively resistant smokers (i.e. no/mild obstruction and minimal emphysema despite heavy smoking), 2) mild upper zone emphysema predominant, 3) airway disease predominant, and 4) severe emphysema. All clusters are strongly associated with COPD-related clinical characteristics, including exacerbations and dyspnea (pCluster analysis identifies four subgroups of smokers that show robust associations with clinical characteristics of COPD and known COPD-associated genetic variants. PMID:24563194

  1. Whole Genome Analysis of Injectional Anthrax Identifies Two Disease Clusters Spanning More Than 13 Years.

    Science.gov (United States)

    Keim, Paul; Grunow, Roland; Vipond, Richard; Grass, Gregor; Hoffmaster, Alex; Birdsell, Dawn N; Klee, Silke R; Pullan, Steven; Antwerpen, Markus; Bayer, Brittany N; Latham, Jennie; Wiggins, Kristin; Hepp, Crystal; Pearson, Talima; Brooks, Tim; Sahl, Jason; Wagner, David M

    2015-11-01

    Anthrax is a rare disease in humans but elicits great public fear because of its past use as an agent of bioterrorism. Injectional anthrax has been occurring sporadically for more than ten years in heroin consumers across multiple European countries and this outbreak has been difficult to trace back to a source. We took a molecular epidemiological approach in understanding this disease outbreak, including whole genome sequencing of Bacillus anthracis isolates from the anthrax victims. We also screened two large strain repositories for closely related strains to provide context to the outbreak. Analyzing 60 Bacillus anthracis isolates associated with injectional anthrax cases and closely related reference strains, we identified 1071 Single Nucleotide Polymorphisms (SNPs). The synapomorphic SNPs (350) were used to reconstruct phylogenetic relationships, infer likely epidemiological sources and explore the dynamics of evolving pathogen populations. Injectional anthrax genomes separated into two tight clusters: one group was exclusively associated with the 2009-10 outbreak and located primarily in Scotland, whereas the second comprised more recent (2012-13) cases but also a single Norwegian case from 2000. Genome-based differentiation of injectional anthrax isolates argues for at least two separate disease events spanning > 12 years. The genomic similarity of the two clusters makes it likely that they are caused by separate contamination events originating from the same geographic region and perhaps the same site of drug manufacturing or processing. Pathogen diversity within single patients challenges assumptions concerning population dynamics of infecting B. anthracis and host defensive barriers for injectional anthrax. This work was supported by the United States Department of Homeland Security grant no. HSHQDC-10-C-00,139 and via a binational cooperative agreement between the United States Government and the Government of Germany. This work was supported by funds

  2. Variability in the sxt Gene Clusters of PSP Toxin Producing Aphanizomenon gracile Strains from Norway, Spain, Germany and North America.

    Science.gov (United States)

    Ballot, Andreas; Cerasino, Leonardo; Hostyeva, Vladyslava; Cirés, Samuel

    2016-01-01

    Paralytic shellfish poisoning (PSP) toxin production has been detected worldwide in the cyanobacterial genera Anabaena, Lyngbya, Scytonema, Cuspidothrix and Aphanizomenon. In Europe Aphanizomenon gracile and Cuspidothrix issatschenkoi are the only known producers of PSP toxins and are found in Southwest and Central European freshwater bodies. In this study the PSP toxin producing Aphanizomenon sp. strain NIVA-CYA 851 was isolated from the Norwegian Lake Hillestadvannet. In a polyphasic approach NIVA-CYA 851 was morphologically and phylogenetically classified, and investigated for toxin production. The strain NIVA-CYA 851 was identified as A. gracile using 16S rRNA gene phylogeny and was confirmed to produce neosaxitoxin, saxitoxin and gonyautoxin 5 by LC-MS. The whole sxt gene clusters (circa 27.3 kb) of four A. gracile strains: NIVA-CYA 851 (Norway); NIVA-CYA 655 & NIVA-CYA 676 (Germany); and UAM 529 (Spain), all from latitudes between 40° and 59° North were sequenced and compared with the sxt gene cluster of reference strain A. gracile NH-5 from the USA. All five sxt gene clusters are highly conserved with similarities exceeding 99.4%, but they differ slightly in the number and presence of single nucleotide polymorphisms (SNPs) and insertions/deletions (In/Dels). Altogether 178 variable sites (44 SNPs and 4 In/Dels, comprising 134 nucleotides) were found in the sxt gene clusters of the Norwegian, German and Spanish strains compared to the reference strain. Thirty-nine SNPs were located in 16 of the 27 coding regions. The sxt gene clusters of NIVA-CYA 851, NIVA-CYA 655, NIVA-CYA 676 and UAM 529, were characterized by 15, 16, 19 and 23 SNPs respectively. Only the Norwegian strain NIVA-CYA 851 possessed an insertion of 126 base pairs (bp) in the noncoding area between the sxtA and sxtE genes and a deletion of 6 nucleotides in the sxtN gene. The sxtI gene showed the highest variability and is recommended as the best genetic marker for further phylogenetic studies

  3. Identification of the nik Gene Cluster of Brucella suis: Regulation and Contribution to Urease Activity

    Science.gov (United States)

    Jubier-Maurin, Véronique; Rodrigue, Agnès; Ouahrani-Bettache, Safia; Layssac, Marion; Mandrand-Berthelot, Marie-Andrée; Köhler, Stephan; Liautard, Jean-Pierre

    2001-01-01

    Analysis of a Brucella suis 1330 gene fused to a gfp reporter, and identified as being induced in J774 murine macrophage-like cells, allowed the isolation of a gene homologous to nikA, the first gene of the Escherichia coli operon encoding the specific transport system for nickel. DNA sequence analysis of the corresponding B. suis nik locus showed that it was highly similar to that of E. coli except for localization of the nikR regulatory gene, which lies upstream from the structural nikABCDE genes and in the opposite orientation. Protein sequence comparisons suggested that the deduced nikABCDE gene products belong to a periplasmic binding protein-dependent transport system. The nikA promoter-gfp fusion was activated in vitro by low oxygen tension and metal ion deficiency and was repressed by NiCl2 excess. Insertional inactivation of nikA strongly reduced the activity of the nickel metalloenzyme urease, which was restored by addition of a nickel excess. Moreover, the nikA mutant of B. suis was functionally complemented with the E. coli nik gene cluster, leading to the recovery of urease activity. Reciprocally, an E. coli strain harboring a deleted nik operon recovered hydrogenase activity by heterologous complementation with the B. suis nik locus. Taking into account these results, we propose that the nik locus of B. suis encodes a nickel transport system. The results further suggest that nickel could enter B. suis via other transport systems. Intracellular growth rates of the B. suis wild-type and nikA mutant strains in human monocytes were similar, indicating that nikA was not essential for this step of infection. We discuss a possible role of nickel transport in maintaining enzymatic activities which could be crucial for survival of the bacteria under the environmental conditions encountered within the host. PMID:11133934

  4. Identifying promoters for gene expression in Clostridium thermocellum

    Directory of Open Access Journals (Sweden)

    Daniel G. Olson

    2015-12-01

    Full Text Available A key tool for metabolic engineering is the ability to express heterologous genes. One obstacle to gene expression in non-model organisms, and especially in relatively uncharacterized bacteria, is the lack of well-characterized promoters. Here we test 17 promoter regions for their ability to drive expression of the reporter genes β-galactosidase (lacZ and NADPH-alcohol dehydrogenase (adhB in Clostridium thermocellum, an important bacterium for the production of cellulosic biofuels. Only three promoters have been commonly used for gene expression in C. thermocellum, gapDH, cbp and eno. Of the new promoters tested, 2638, 2926, 966 and 815 showed reliable expression. The 2638 promoter showed relatively higher activity when driving adhB (compared to lacZ, and the 815 promoter showed relatively higher activity when driving lacZ (compared to adhB.

  5. Clustered organization, polycistronic transcription, and evolution of modification-guide snoRNA genes in Euglena gracilis.

    Science.gov (United States)

    Moore, Ashley N; Russell, Anthony G

    2012-01-01

    Previous studies have shown that the eukaryotic microbe Euglena gracilis contains an unusually large assortment of small nucleolar RNAs (snoRNAs) and ribosomal RNA (rRNA) modification sites. However, little is known about the evolutionary mechanisms contributing to this situation. In this study, we have examined the organization and evolution of snoRNA genes in Euglena with the additional objective of determining how these properties relate to the rRNA modification pattern in this protist. We have identified and extensively characterized a clustered pattern of genes encoding previously biochemically isolated snoRNA sequences in E. gracilis. We show that polycistronic transcription is a prevalent snoRNA gene expression strategy in this organism. Further, we have identified 121 new snoRNA coding regions through sequence analysis of these clusters. We have identified an E. gracilis U14 snoRNA homolog clustered with modification-guide snoRNA genes. The U14 snoRNAs in other eukaryotic organisms examined to date typically contain both a modification and a processing domain. E. gracilis U14 lacks the modification domain but retains the processing domain. Our analysis of U14 structure and evolution in Euglena and other eukaryotes allows us to propose a model for its evolution and suggest its processing role may be its more important function, explaining its conservation in many eukaryotes. The preponderance of apparent small and larger-scale duplication events in the genomic regions we have characterized in Euglena provides a mechanism for the generation of the unusually diverse collection and abundance of snoRNAs and modified rRNA sites. Our findings provide the framework for more extensive whole genome analysis to elucidate whether these snoRNA gene clusters are spread across multiple chromosomes and/or form dense "arrays" at a limited number of chromosomal loci.

  6. 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...

  7. Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics.