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

Science.gov (United States)

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

2005-03-01

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

Co-evolution of secondary metabolite gene clusters and their host

DEFF Research Database (Denmark)

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

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

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

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Gardiner Donald M

2007-09-01

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

Localization and orientation of heavy-atom cluster compounds in protein crystals using molecular replacement

International Nuclear Information System (INIS)

Dahms, Sven O.; Kuester, Miriam; Streb, Carsten; Roth, Christian; Sträter, Norbert; Than, Manuel E.

2013-01-01

A new approach is presented that allows the efficient localization and orientation of heavy-atom cluster compounds used in experimental phasing by a molecular replacement procedure. This permits the calculation of meaningful phases up to the highest resolution of the diffraction data. Heavy-atom clusters (HA clusters) containing a large number of specifically arranged electron-dense scatterers are especially useful for experimental phase determination of large complex structures, weakly diffracting crystals or structures with large unit cells. Often, the determination of the exact orientation of the HA cluster and hence of the individual heavy-atom positions proves to be the critical step in successful phasing and subsequent structure solution. Here, it is demonstrated that molecular replacement (MR) with either anomalous or isomorphous differences is a useful strategy for the correct placement of HA cluster compounds. The polyoxometallate cluster hexasodium α-metatungstate (HMT) was applied in phasing the structure of death receptor 6. Even though the HA cluster is bound in alternate partially occupied orientations and is located at a special position, its correct localization and orientation could be determined at resolutions as low as 4.9 Å. The broad applicability of this approach was demonstrated for five different derivative crystals that included the compounds tantalum tetradecabromide and trisodium phosphotungstate in addition to HMT. The correct placement of the HA cluster depends on the length of the intramolecular vectors chosen for MR, such that both a larger cluster size and the optimal choice of the wavelength used for anomalous data collection strongly affect the outcome

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

Science.gov (United States)

Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N

2017-01-04

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

Science.gov (United States)

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

2015-07-01

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

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

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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.

Localization and orientation of heavy-atom cluster compounds in protein crystals using molecular replacement.

Science.gov (United States)

Dahms, Sven O; Kuester, Miriam; Streb, Carsten; Roth, Christian; Sträter, Norbert; Than, Manuel E

2013-02-01

Heavy-atom clusters (HA clusters) containing a large number of specifically arranged electron-dense scatterers are especially useful for experimental phase determination of large complex structures, weakly diffracting crystals or structures with large unit cells. Often, the determination of the exact orientation of the HA cluster and hence of the individual heavy-atom positions proves to be the critical step in successful phasing and subsequent structure solution. Here, it is demonstrated that molecular replacement (MR) with either anomalous or isomorphous differences is a useful strategy for the correct placement of HA cluster compounds. The polyoxometallate cluster hexasodium α-metatungstate (HMT) was applied in phasing the structure of death receptor 6. Even though the HA cluster is bound in alternate partially occupied orientations and is located at a special position, its correct localization and orientation could be determined at resolutions as low as 4.9 Å. The broad applicability of this approach was demonstrated for five different derivative crystals that included the compounds tantalum tetradecabromide and trisodium phosphotungstate in addition to HMT. The correct placement of the HA cluster depends on the length of the intramolecular vectors chosen for MR, such that both a larger cluster size and the optimal choice of the wavelength used for anomalous data collection strongly affect the outcome.

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...

Fast gene ontology based clustering for microarray experiments.

Science.gov (United States)

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

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

Hox gene clusters in the Indonesian coelacanth, Latimeria menadoensis

Science.gov (United States)

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

2003-01-01

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

Orientation, distance, regulation and function of neighbouring genes

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Gherman Adrian

2009-01-01

Full Text Available Abstract The sequencing of the human genome has allowed us to observe globally and in detail the arrangement of genes along the chromosomes. There are multiple lines of evidence that this arrangement is not random, both in terms of intergenic distances and orientation of neighbouring genes. We have undertaken a systematic evaluation of the spatial distribution and orientation of known genes across the human genome. We used genome-level information, including phylogenetic conservation, single nucleotide polymorphism density and correlation of gene expression to assess the importance of this distribution. In addition to confirming and extending known properties of the genome, such as the significance of gene deserts and the importance of 'head to head' orientation of gene pairs in proximity, we provide significant new observations that include a smaller average size for intervals separating the 3' ends of neighbouring genes, a correlation of gene expression across tissues for genes as far as 100 kilobases apart and signatures of increasing positive selection with decreasing interval size surprisingly relaxing for intervals smaller than ~500 base pairs. Further, we provide extensive graphical representations of the genome-wide data to allow for observations and comparisons beyond what we address.

Conditions for the Evolution of Gene Clusters in Bacterial Genomes

Science.gov (United States)

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

2010-01-01

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

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

Science.gov (United States)

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

2015-07-14

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

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

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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.

Conditions for the evolution of gene clusters in bacterial genomes.

Directory of Open Access Journals (Sweden)

Sara Ballouz

2010-02-01

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

Fast Gene Ontology based clustering for microarray experiments

Directory of Open Access Journals (Sweden)

Ovaska Kristian

2008-11-01

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

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

Science.gov (United States)

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

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

Characterization of a multicopper oxidase gene cluster in Phanerochaete chrysosporium and evidence of altered splicing of the mco transcripts

Science.gov (United States)

Luis F. Larrondo; Bernardo Gonzalez; Dan Cullen; Rafael Vicuna

2004-01-01

A cluster of multicopper oxidase genes (mco1, mco2, mco3, mco4) from the lignin-degrading basidiomycete Phanerochaete chrysosporium is described. The four genes share the same transcriptional orientation within a 25 kb region. mco1, mco2 and mco3 are tightly grouped, with intergenic regions of 2.3 and 0.8 kb, respectively, whereas mco4 is located 11 kb upstream of mco1...

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

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

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.

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

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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

Modulated modularity clustering as an exploratory tool for functional genomic inference.

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Eric A Stone

2009-05-01

Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

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

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Boldogköi, Zsolt

2012-01-01

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

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

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Zsolt eBoldogkoi

2012-07-01

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

Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools

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Laganà, Alessandro; Shasha, Dennis; Croce, Carlo Maria

2014-01-01

The use of synthetic non-coding RNAs for post-transcriptional regulation of gene expression has not only become a standard laboratory tool for gene functional studies but it has also opened up new perspectives in the design of new and potentially promising therapeutic strategies. Bioinformatics has provided researchers with a variety of tools for the design, the analysis, and the evaluation of RNAi agents such as small-interfering RNA (siRNA), short-hairpin RNA (shRNA), artificial microRNA (a-miR), and microRNA sponges. More recently, a new system for genome engineering based on the bacterial CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats), was shown to have the potential to also regulate gene expression at both transcriptional and post-transcriptional level in a more specific way. In this mini review, we present RNAi and CRISPRi design principles and discuss the advantages and limitations of the current design approaches.

Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools

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Laganà, Alessandro [Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH (United States); Shasha, Dennis [Courant Institute of Mathematical Sciences, New York University, New York, NY (United States); Croce, Carlo Maria [Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH (United States)

2014-12-11

The use of synthetic non-coding RNAs for post-transcriptional regulation of gene expression has not only become a standard laboratory tool for gene functional studies but it has also opened up new perspectives in the design of new and potentially promising therapeutic strategies. Bioinformatics has provided researchers with a variety of tools for the design, the analysis, and the evaluation of RNAi agents such as small-interfering RNA (siRNA), short-hairpin RNA (shRNA), artificial microRNA (a-miR), and microRNA sponges. More recently, a new system for genome engineering based on the bacterial CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats), was shown to have the potential to also regulate gene expression at both transcriptional and post-transcriptional level in a more specific way. In this mini review, we present RNAi and CRISPRi design principles and discuss the advantages and limitations of the current design approaches.

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

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

2002-12-12

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

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

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

2017-08-01

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

Functional clustering of time series gene expression data by Granger causality

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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

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

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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.

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

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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.

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

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

2014-01-01

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

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

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Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A scale invariant clustering of genes on human chromosome 7

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Kendal Wayne S

2004-01-01

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

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

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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.

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

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Gong Binsheng

2011-05-01

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

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

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Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

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

A fast, dataflow-oriented preprocessor for cluster counting

International Nuclear Information System (INIS)

Imhof, M.

1995-01-01

One of the main problems in the use of cluster counting for particle identification in high energy physics is the huge primary data rate. By means of an online data reduction system, this data rate can be reduced to the amount known from conventional integral charge/time readout. For tests and optimization of online data reduction algorithms, a RISC-based, data-flow-oriented multiprocessor board has been designed. (orig.)

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

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

2012-07-15

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

Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

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Olszewski Kellen L

2007-07-01

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

A highly accurate positioning and orientation system based on the usage of four-cluster fibre optic gyros

International Nuclear Information System (INIS)

Zhang, Xiaoyue; Lin, Zhili; Zhang, Chunxi

2013-01-01

A highly accurate positioning and orientation technique based on four-cluster fibre optic gyros (FOGs) is presented. The four-cluster FOG inertial measurement unit (IMU) comprises three low-precision FOGs, one static high-precision FOG and three accelerometers. To realize high-precision positioning and orientation, the static alignment (north-seeking) before vehicle manoeuvre was divided into a low-precision self-alignment phase and a high-precision north-seeking (online calibration) phase. The high-precision FOG measurement information was introduced to obtain high-precision azimuth alignment (north-seeking) result and achieve online calibration of the low-precision three-cluster FOG. The results of semi-physical simulation were presented to validate the availability and utility of the highly accurate positioning and orientation technique based on the four-cluster FOGs. (paper)

Unusual Gene Order and Organization of the Sea Urchin HoxCluster

Energy Technology Data Exchange (ETDEWEB)

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

2005-05-10

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

Analysis of genetic association using hierarchical clustering and cluster validation indices.

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Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

2017-10-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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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

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

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

2017-01-01

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

Calcitonin gene-related peptide antagonism and cluster headache

DEFF Research Database (Denmark)

Ashina, Håkan; Newman, Lawrence; Ashina, Sait

2017-01-01

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

Network Analysis Tools: from biological networks to clusters and pathways.

Science.gov (United States)

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Composition and genomic organization of arthropod Hox clusters.

Science.gov (United States)

Pace, Ryan M; Grbić, Miodrag; Nagy, Lisa M

2016-01-01

The ancestral arthropod is believed to have had a clustered arrangement of ten Hox genes. Within arthropods, Hox gene mutations result in transformation of segment identities. Despite the fact that variation in segment number/character was common in the diversification of arthropods, few examples of Hox gene gains/losses have been correlated with morphological evolution. Furthermore, a full appreciation of the variation in the genomic arrangement of Hox genes in extant arthropods has not been recognized, as genome sequences from each major arthropod clade have not been reported until recently. Initial genomic analysis of the chelicerate Tetranychus urticae suggested that loss of Hox genes and Hox gene clustering might be more common than previously assumed. To further characterize the genomic evolution of arthropod Hox genes, we compared the genomic arrangement and general characteristics of Hox genes from representative taxa from each arthropod subphylum. In agreement with others, we find arthropods generally contain ten Hox genes arranged in a common orientation in the genome, with an increasing number of sampled species missing either Hox3 or abdominal-A orthologs. The genomic clustering of Hox genes in species we surveyed varies significantly, ranging from 0.3 to 13.6 Mb. In all species sampled, arthropod Hox genes are dispersed in the genome relative to the vertebrate Mus musculus. Differences in Hox cluster size arise from variation in the number of intervening genes, intergenic spacing, and the size of introns and UTRs. In the arthropods surveyed, Hox gene duplications are rare and four microRNAs are, in general, conserved in similar genomic positions relative to the Hox genes. The tightly clustered Hox complexes found in the vertebrates are not evident within arthropods, and differential patterns of Hox gene dispersion are found throughout the arthropods. The comparative genomic data continue to support an ancestral arthropod Hox cluster of ten genes with

CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

DEFF Research Database (Denmark)

G. G. Nielsen, Fiona; Galschiøt Markus, Kasper; Møllegaard Friborg, Rune

2012-01-01

IP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon...... a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns...... it an invaluable tool for explorative research based on ChIP profiling data. CATCHprofiles and the CATCH algorithm run on all platforms and is available for free through the CATCH website: http://catch.cmbi.ru.nl/. User support is available by subscribing to the mailing list catch-users@bioinformatics.org....

Extension of an Object-Oriented Optimization Tool: User's Reference Manual

Science.gov (United States)

Pak, Chan-Gi; Truong, Samson S.

2015-01-01

The National Aeronautics and Space Administration Armstrong Flight Research Center has developed a cost-effective and flexible object-oriented optimization (O (sup 3)) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. This object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the O (sup 3) tool and the discipline modules, or both. Six different sample mathematical problems are presented to demonstrate the performance of the O (sup 3) tool. Instructions for preparing input data for the O (sup 3) tool are detailed in this user's manual.

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.

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

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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.

Online Analytical Processing (OLAP: A Fast and Effective Data Mining Tool for Gene Expression Databases

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Alkharouf Nadim W.

2005-01-01

Full Text Available Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD. A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

Online analytical processing (OLAP): a fast and effective data mining tool for gene expression databases.

Science.gov (United States)

Alkharouf, Nadim W; Jamison, D Curtis; Matthews, Benjamin F

2005-06-30

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

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

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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.

Comparative analysis of clustering methods for gene expression time course data

Directory of Open Access Journals (Sweden)

Ivan G. Costa

2004-01-01

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

Evaluation of gene-expression clustering via mutual information distance measure

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Maimon Oded

2007-03-01

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

Minimum Information about a Biosynthetic Gene cluster : commentary

NARCIS (Netherlands)

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

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

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.

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

Science.gov (United States)

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

2016-01-01

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

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...

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

Science.gov (United States)

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

2009-06-16

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

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

Science.gov (United States)

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

2012-01-01

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

Integration of the Gene Ontology into an object-oriented architecture

Directory of Open Access Journals (Sweden)

Zheng W Jim

2005-05-01

Full Text Available Abstract Background To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Results Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta receptor complex assembly" (GO:0007181. Conclusion We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

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

Science.gov (United States)

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

2004-01-01

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

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

Science.gov (United States)

Schulz, Tizian; Stoye, Jens; Doerr, Daniel

2018-05-08

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

Automatic Semantic Orientation of Adjectives for Indonesian Language Using PMI-IR and Clustering

Science.gov (United States)

Riyanti, Dewi; Arif Bijaksana, M.; Adiwijaya

2018-03-01

We present our work in the area of sentiment analysis for Indonesian language. We focus on bulding automatic semantic orientation using available resources in Indonesian. In this research we used Indonesian corpus that contains 9 million words from kompas.txt and tempo.txt that manually tagged and annotated with of part-of-speech tagset. And then we construct a dataset by taking all the adjectives from the corpus, removing the adjective with no orientation. The set contained 923 adjective words. This systems will include several steps such as text pre-processing and clustering. The text pre-processing aims to increase the accuracy. And finally clustering method will classify each word to related sentiment which is positive or negative. With improvements to the text preprocessing, can be achieved 72% of accuracy.

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

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

Science.gov (United States)

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

2017-12-01

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

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

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

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

International Nuclear Information System (INIS)

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

1990-01-01

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

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

NARCIS (Netherlands)

Blom van Assendelft, Margaretha van

1989-01-01

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

Social media as a marketing tool for extreme-sport oriented companies

OpenAIRE

Korosuo, Saku

2013-01-01

Marketing in social media has been studied extensively in recent years, but not specifically for extreme-sport oriented companies. Even though most of the extreme-oriented companies are using social media for marketing, only a few pay special attention to its risks and possibilities. The purpose of this study is to identify extreme-sport oriented companies' practices to use social media as a marketing tool. I interviewed eight extreme- oriented companies and athletes. In addition to interview...

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

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

associated with MeSH terms. MeSH terms can be associated with genes through co-occurrence of these in MEDLINE citations, i.e. the genes occur in titles or abstracts and the MeSH terms are assigned by experts. To identify MeSH terms associated with a group of genes we used the tool MESHGENE developed at the Information Dynamics Lab at HP Labs (http://www-idl.hpl.hp.com/meshgene/). When presented with a list of human genes, MESHGENE uses some sophisticated techniques to search for these gene symbols in the titles and abstracts of all MEDLINE citations. MeSH terms and the number of co-occurrences can be retrieved. Gene symbols that are aliases of each other are pooled from several databases. This addresses the problem of synonymy, the fact that several symbols can refer to the same gene. MESHGENE employs some sophisticated algorithms that disregards symbols that are likely to be acronyms for other concepts than a gene. This addresses the problem of polysemy, i.e. possible multiple meanings of a gene symbol. We applied our approach to gene expression data from herpes virus infected human fibroblast cells. The data contains 12 time-points, between 1/2 hrs and 48 hrs after infection. Singular Value Decomposition was used to identify the dominant modes of expression. 75% of the variance in the expression data was captured by the first two modes, the first exhibiting a monotonly increasing expression pattern and the second a more transient pattern. Projection of the gene expression vectors onto this first two modes identified 3 statistically significant clusters of co-expressed genes. 500 genes from cluster 1 and 300 genes from clusters 2 and 3 each were uploaded to MESHGENE and the MeSH terms and co-occurrence values were retrieved. MeSH terms were also obtained for 5 groups of randomly selected genes with similar numbers of genes. The log was taken of the co-occurrence values and for each MeSH term these log co-occurrence values were summed for each group over the genes in that

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

Science.gov (United States)

Mazandu, Gaston K; Mulder, Nicola J

2013-09-25

The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

GENECODIS-Grid: An online grid-based tool to predict functional information in gene lists

International Nuclear Information System (INIS)

Nogales, R.; Mejia, E.; Vicente, C.; Montes, E.; Delgado, A.; Perez Griffo, F. J.; Tirado, F.; Pascual-Montano, A.

2007-01-01

In this work we introduce GeneCodis-Grid, a grid-based alternative to a bioinformatics tool named Genecodis that integrates different sources of biological information to search for biological features (annotations) that frequently co-occur in a set of genes and rank them by statistical significance. GeneCodis-Grid is a web-based application that takes advantage of two independent grid networks and a computer cluster managed by a meta-scheduler and a web server that host the application. The mining of concurrent biological annotations provides significant information for the functional analysis of gene list obtained by high throughput experiments in biology. Due to the large popularity of this tool, that has registered more than 13000 visits since its publication in January 2007, there is a strong need to facilitate users from different sites to access the system simultaneously. In addition, the complexity of some of the statistical tests used in this approach has made this technique a good candidate for its implementation in a Grid opportunistic environment. (Author)

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

Science.gov (United States)

Liu, Xiao; Shi, Jun; Wang, Congzhi

2015-01-01

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

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

KAUST Repository

Li, Yongxin

2015-03-24

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

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

Science.gov (United States)

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

2015-03-01

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

Conservation of gene linkage in dispersed vertebrate NK homeobox clusters.

Science.gov (United States)

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

2009-10-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-05-12

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

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

Science.gov (United States)

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

2014-12-01

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

HOXA genes cluster: clinical implications of the smallest deletion

OpenAIRE

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

2015-01-01

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

G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

Science.gov (United States)

In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

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

Directory of Open Access Journals (Sweden)

Sakellariou Argiris

2012-10-01

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

Clustering gene expression regulators: new approach to disease subtyping.

Directory of Open Access Journals (Sweden)

Mikhail Pyatnitskiy

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

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.

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.

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

Science.gov (United States)

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

2015-01-01

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

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

Energy Technology Data Exchange (ETDEWEB)

Chen, I-Min; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Huang, Jinghua; Reddy, T. B.K.; Cimermancic, Peter; Fischbach, Michael; Ivanova, Natalia; Markowitz, Victor; Kyrpides, Nikos; Pati, Amrita

2014-10-28

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorway to a new era in the discovery of novel molecules.

Experience with case tools in the design of process-oriented software

Science.gov (United States)

Novakov, Ognian; Sicard, Claude-Henri

1994-12-01

In Accelerator systems such as the CERN PS complex, process equipment has a life time which may exceed the typical life cycle of its related software. Taking into account the variety of such equipment, it is important to keep the analysis and design of the software in a system-independent form. This paper discusses the experience gathered in using commercial CASE tools for analysis, design and reverse engineering of different process-oriented software modules, with a principal emphasis on maintaining the initial analysis in a standardized form. Such tools have been in existence for several years, but this paper shows that they are not fully adapted to our needs. In particular, the paper stresses the problems of integrating such a tool into an existing data-base-dependent development chain, the lack of real-time simulation tools and of Object-Oriented concepts in existing commercial packages. Finally, the paper gives a broader view of software engineering needs in our particular context.

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

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Irigoien Itziar

2012-02-01

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

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

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P.Balaji

2015-01-01

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

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

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

2017-01-01

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

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 ...

Evolution of the C-Type Lectin-Like Receptor Genes of the DECTIN-1 Cluster in the NK Gene Complex

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Susanne Sattler

2012-01-01

Full Text Available Pattern recognition receptors are crucial in initiating and shaping innate and adaptive immune responses and often belong to families of structurally and evolutionarily related proteins. The human C-type lectin-like receptors encoded in the DECTIN-1 cluster within the NK gene complex contain prominent receptors with pattern recognition function, such as DECTIN-1 and LOX-1. All members of this cluster share significant homology and are considered to have arisen from subsequent gene duplications. Recent developments in sequencing and the availability of comprehensive sequence data comprising many species showed that the receptors of the DECTIN-1 cluster are not only homologous to each other but also highly conserved between species. Even in Caenorhabditis elegans, genes displaying homology to the mammalian C-type lectin-like receptors have been detected. In this paper, we conduct a comprehensive phylogenetic survey and give an up-to-date overview of the currently available data on the evolutionary emergence of the DECTIN-1 cluster genes.

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

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

2018-05-18

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

Homo-FRET imaging as a tool to quantify protein and lipid clustering.

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Bader, Arjen N; Hoetzl, Sandra; Hofman, Erik G; Voortman, Jarno; van Bergen en Henegouwen, Paul M P; van Meer, Gerrit; Gerritsen, Hans C

2011-02-25

Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical proteins and lipids. Homo-FRET imaging has the ability to determine distances between fluorophores. In addition it can be employed to quantify cluster sizes as well as cluster size distributions. The interpretation of homo-FRET signals is complicated by the fact that both the mutual orientations of the fluorophores and the number of fluorophores per cluster affect the fluorescence anisotropy in a similar way. The properties of the fluorescence probes are very important. Taking these properties into account is critical for the correct interpretation of homo-FRET signals in protein- and lipid-clustering studies. This is be exemplified by studies on the clustering of the lipid raft markers GPI and K-ras, as well as for EGF receptor clustering in the plasma membrane. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GenClust: A genetic algorithm for clustering gene expression data

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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.

Cluster Flow: A user-friendly bioinformatics workflow tool [version 1; referees: 3 approved

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Philip Ewels

2016-12-01

Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

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.

piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

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Ray, Rishav; Pandey, Priyanka

2017-12-19

With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Clustering-based approaches to SAGE data mining

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Wang Haiying

2008-07-01

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

fcGENE: a versatile tool for processing and transforming SNP datasets.

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Nab Raj Roshyara

Full Text Available Modern analysis of high-dimensional SNP data requires a number of biometrical and statistical methods such as pre-processing, analysis of population structure, association analysis and genotype imputation. Software used for these purposes often rely on specific and incompatible input and output data formats. Therefore extensive data management including multiple format conversions is necessary during analyses.In order to support fast and efficient management and bio-statistical quality control of high-dimensional SNP data, we developed the publically available software fcGENE using C++ object-oriented programming language. This software simplifies and automates the use of different existing analysis packages, especially during the workflow of genotype imputations and corresponding analyses.fcGENE transforms SNP data and imputation results into different formats required for a large variety of analysis packages such as PLINK, SNPTEST, HAPLOVIEW, EIGENSOFT, GenABEL and tools used for genotype imputation such as MaCH, IMPUTE, BEAGLE and others. Data Management tasks like merging, splitting, extracting SNP and pedigree information can be performed. fcGENE also supports a number of bio-statistical quality control processes and quality based filtering processes at SNP- and sample-wise level. The tool also generates templates of commands required to run specific software packages, especially those required for genotype imputation. We demonstrate the functionality of fcGENE by example workflows of SNP data analyses and provide a comprehensive manual of commands, options and applications.We have developed a user-friendly open-source software fcGENE, which comprehensively supports SNP data management, quality control and analysis workflows. Download statistics and corresponding feedbacks indicate that software is highly recognised and extensively applied by the scientific community.

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

NARCIS (Netherlands)

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

2008-01-01

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

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

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

1998-08-01

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

Two Gene Clusters Coordinate Galactose and Lactose Metabolism in Streptococcus gordonii

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Zeng, Lin; Martino, Nicole C.

2012-01-01

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

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

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He eLiu

2014-10-01

Full Text Available Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay (EMSA demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, SOD and catalase activity, and oxide detoxicating ability.

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress.

Science.gov (United States)

Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

2014-01-01

Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, superoxide dismutase and catalase activity, and oxide detoxicating ability.

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

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Adelson David L

2009-04-01

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

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

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

2006-03-01

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

Interacting orientations and instrumentalities to adapt a learning tool for health professionals

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Kathrine L. Nygård

2015-09-01

Full Text Available Web-based instructional software offers new opportunities for collaborative, task-oriented in-service training. Planning and negotiation of content to adapt a web-based learning resource for nursing is the topic of this paper. We draw from Cultural Historical Activity Theory to elaborate the dialectical relationship of changing and stabilizing organizational practice. Local adaptation to create a domain-specific resource plays out as interactions of orientations and instrumentalities. Our analysis traces how orientations, i.e., in situ selection of knowledge and mobilization of experiences, and instrumentality, i.e., interpreted affordances of available cultural tools, interact. The adaptation processes are mediated by a set of new and current tools that interact with multiple orientations to ensure stability and promote change. Practice and project are introduced as intermediate, analytic concepts to assess tensions in the observed activity. Our analysis shows three central tensions, how they are introduced, addressed and subsequently resolved. Considering the opportunities help understand how engagement with technology can lead to new representations for introduction to a local knowledge domain.

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.

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

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

2005-02-01

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

cluML: A markup language for clustering and cluster validity assessment of microarray data.

Science.gov (United States)

Bolshakova, Nadia; Cunningham, Pádraig

2005-01-01

cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

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

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Westerdahl Ann-Charlotte

2010-06-01

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

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

Science.gov (United States)

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

2010-06-09

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

Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

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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.

Lightweight object oriented structure analysis: tools for building tools to analyze molecular dynamics simulations.

Science.gov (United States)

Romo, Tod D; Leioatts, Nicholas; Grossfield, Alan

2014-12-15

LOOS (Lightweight Object Oriented Structure-analysis) is a C++ library designed to facilitate making novel tools for analyzing molecular dynamics simulations by abstracting out the repetitive tasks, allowing developers to focus on the scientifically relevant part of the problem. LOOS supports input using the native file formats of most common biomolecular simulation packages, including CHARMM, NAMD, Amber, Tinker, and Gromacs. A dynamic atom selection language based on the C expression syntax is included and is easily accessible to the tool-writer. In addition, LOOS is bundled with over 140 prebuilt tools, including suites of tools for analyzing simulation convergence, three-dimensional histograms, and elastic network models. Through modern C++ design, LOOS is both simple to develop with (requiring knowledge of only four core classes and a few utility functions) and is easily extensible. A python interface to the core classes is also provided, further facilitating tool development. © 2014 Wiley Periodicals, Inc.

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

Science.gov (United States)

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

2013-01-01

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

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

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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

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

Directory of Open Access Journals (Sweden)

Scherer Stephen W

2011-05-01

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

Orienting the Neighborhood: A Subdivision Energy Analysis Tool

Energy Technology Data Exchange (ETDEWEB)

Christensen, C.; Horowitz, S.

2008-01-01

In subdivisions, house orientations are largely determined by street layout. The resulting house orientations affect energy consumption (annual and on-peak) for heating and cooling, depending on window area distributions and shading from neighboring houses. House orientations also affect energy production (annual and on-peak) from solar thermal and photovoltaic systems, depending on available roof surfaces. Therefore, house orientations fundamentally influence both energy consumption and production, and an appropriate street layout is a prerequisite for taking full advantage of energy efficiency and renewable energy opportunities. The potential influence of street layout on solar performance is often acknowledged, but solar and energy issues must compete with many other criteria and constraints that influence subdivision street layout. When only general guidelines regarding energy are available, these factors may be ignored or have limited effect. Also, typical guidelines are often not site-specific and do not account for local parameters such as climate and the time value of energy. For energy to be given its due consideration in subdivision design, energy impacts need to be accurately quantified and displayed interactively to facilitate analysis of design alternatives. This paper describes a new computerized Subdivision Energy Analysis Tool being developed to allow users to interactively design subdivision street layouts while receiving feedback about energy impacts based on user-specified building design variants and availability of roof surfaces for photovoltaic and solar water heating systems.

Development of probabilistic thinking-oriented learning tools for probability materials at junior high school students

Science.gov (United States)

Sari, Dwi Ivayana; Hermanto, Didik

2017-08-01

This research is a developmental research of probabilistic thinking-oriented learning tools for probability materials at ninth grade students. This study is aimed to produce a good probabilistic thinking-oriented learning tools. The subjects were IX-A students of MTs Model Bangkalan. The stages of this development research used 4-D development model which has been modified into define, design and develop. Teaching learning tools consist of lesson plan, students' worksheet, learning teaching media and students' achievement test. The research instrument used was a sheet of learning tools validation, a sheet of teachers' activities, a sheet of students' activities, students' response questionnaire and students' achievement test. The result of those instruments were analyzed descriptively to answer research objectives. The result was teaching learning tools in which oriented to probabilistic thinking of probability at ninth grade students which has been valid. Since teaching and learning tools have been revised based on validation, and after experiment in class produced that teachers' ability in managing class was effective, students' activities were good, students' responses to the learning tools were positive and the validity, sensitivity and reliability category toward achievement test. In summary, this teaching learning tools can be used by teacher to teach probability for develop students' probabilistic thinking.

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

Science.gov (United States)

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

2017-08-01

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

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

NARCIS (Netherlands)

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

2010-01-01

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

Targeted capture and heterologous expression of the Pseudoalteromonas alterochromide gene cluster in Escherichia coli represents a promising natural product exploratory platform.

Science.gov (United States)

Ross, Avena C; Gulland, Lauren E S; Dorrestein, Pieter C; Moore, Bradley S

2015-04-17

Marine pseudoalteromonads represent a very promising source of biologically important natural product molecules. To access and exploit the full chemical capacity of these cosmopolitan Gram-(-) bacteria, we sought to apply universal synthetic biology tools to capture, refactor, and express biosynthetic gene clusters for the production of complex organic compounds in reliable host organisms. Here, we report a platform for the capture of proteobacterial gene clusters using a transformation-associated recombination (TAR) strategy coupled with direct pathway manipulation and expression in Escherichia coli. The ~34 kb pathway for production of alterochromide lipopeptides by Pseudoalteromonas piscicida JCM 20779 was captured and heterologously expressed in E. coli utilizing native and E. coli-based T7 promoter sequences. Our approach enabled both facile production of the alterochromides and in vivo interrogation of gene function associated with alterochromide's unusual brominated lipid side chain. This platform represents a simple but effective strategy for the discovery and biosynthetic characterization of natural products from marine proteobacteria.

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

Educational clusters as a tool ofpublic policy on the market of educational services

OpenAIRE

M. I. Vorona

2016-01-01

Due to the new challenges, the implementation of cluster technology can be considired to be one of the innovative and promising tools of national and regional economy’ competitiveness raise. The cluster approach can be used is in different areas, but most attention in thie article has been paid to the problems of industrial clusters. At the same time, educational clusters remain to be poorly implemented in practice and, consequently, they are less studied theoretically. The aim of the arti...

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Analysis of unemployment regulation tools oriented towards labour supply in Lithuania

OpenAIRE

Šakienė, Henrika

2011-01-01

The need of unemployment regulation is very important issue nowadays. Unemployment regulation tools can be address towards labour supply either demand. Recently opened scientists discussion about growing need to regulate labour supply because of high volunteer caused unemployment and situation when open work places cannot be filled with existing labour supply because of the various reasons. This article objective is to review possible unemployment regulation tools oriented towards labour supp...

Cluster analysis as a prediction tool for pregnancy outcomes.

Science.gov (United States)

Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

2015-03-01

Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

Gene Repression in Haloarchaea Using the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas I-B System.

Science.gov (United States)

Stachler, Aris-Edda; Marchfelder, Anita

2016-07-15

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system is used by bacteria and archaea to fend off foreign genetic elements. Since its discovery it has been developed into numerous applications like genome editing and regulation of transcription in eukaryotes and bacteria. For archaea currently no tools for transcriptional repression exist. Because molecular biology analyses in archaea become more and more widespread such a tool is vital for investigating the biological function of essential genes in archaea. Here we use the model archaeon Haloferax volcanii to demonstrate that its endogenous CRISPR-Cas system I-B can be harnessed to repress gene expression in archaea. Deletion of cas3 and cas6b genes results in efficient repression of transcription. crRNAs targeting the promoter region reduced transcript levels down to 8%. crRNAs targeting the reading frame have only slight impact on transcription. crRNAs that target the coding strand repress expression only down to 88%, whereas crRNAs targeting the template strand repress expression down to 8%. Repression of an essential gene results in reduction of transcription levels down to 22%. Targeting efficiencies can be enhanced by expressing a catalytically inactive Cas3 mutant. Genes can be targeted on plasmids or on the chromosome, they can be monocistronic or part of a polycistronic operon. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Gene Repression in Haloarchaea Using the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas I-B System*

Science.gov (United States)

Stachler, Aris-Edda; Marchfelder, Anita

2016-01-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system is used by bacteria and archaea to fend off foreign genetic elements. Since its discovery it has been developed into numerous applications like genome editing and regulation of transcription in eukaryotes and bacteria. For archaea currently no tools for transcriptional repression exist. Because molecular biology analyses in archaea become more and more widespread such a tool is vital for investigating the biological function of essential genes in archaea. Here we use the model archaeon Haloferax volcanii to demonstrate that its endogenous CRISPR-Cas system I-B can be harnessed to repress gene expression in archaea. Deletion of cas3 and cas6b genes results in efficient repression of transcription. crRNAs targeting the promoter region reduced transcript levels down to 8%. crRNAs targeting the reading frame have only slight impact on transcription. crRNAs that target the coding strand repress expression only down to 88%, whereas crRNAs targeting the template strand repress expression down to 8%. Repression of an essential gene results in reduction of transcription levels down to 22%. Targeting efficiencies can be enhanced by expressing a catalytically inactive Cas3 mutant. Genes can be targeted on plasmids or on the chromosome, they can be monocistronic or part of a polycistronic operon. PMID:27226589

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

Directory of Open Access Journals (Sweden)

Jason C Slot

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

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

OpenAIRE

Ehrlich, Kenneth C.; Mack, Brian M.

2014-01-01

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

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

OpenAIRE

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

2018-01-01

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

Identification of the Regulator Gene Responsible for the Acetone-Responsive Expression of the Binuclear Iron Monooxygenase Gene Cluster in Mycobacteria ▿

Science.gov (United States)

Furuya, Toshiki; Hirose, Satomi; Semba, Hisashi; Kino, Kuniki

2011-01-01

The mimABCD gene cluster encodes the binuclear iron monooxygenase that oxidizes propane and phenol in Mycobacterium smegmatis strain MC2 155 and Mycobacterium goodii strain 12523. Interestingly, expression of the mimABCD gene cluster is induced by acetone. In this study, we investigated the regulator gene responsible for this acetone-responsive expression. In the genome sequence of M. smegmatis strain MC2 155, the mimABCD gene cluster is preceded by a gene designated mimR, which is divergently transcribed. Sequence analysis revealed that MimR exhibits amino acid similarity with the NtrC family of transcriptional activators, including AcxR and AcoR, which are involved in acetone and acetoin metabolism, respectively. Unexpectedly, many homologs of the mimR gene were also found in the sequenced genomes of actinomycetes. A plasmid carrying a transcriptional fusion of the intergenic region between the mimR and mimA genes with a promoterless green fluorescent protein (GFP) gene was constructed and introduced into M. smegmatis strain MC2 155. Using a GFP reporter system, we confirmed by deletion and complementation analyses that the mimR gene product is the positive regulator of the mimABCD gene cluster expression that is responsive to acetone. M. goodii strain 12523 also utilized the same regulatory system as M. smegmatis strain MC2 155. Although transcriptional activators of the NtrC family generally control transcription using the σ54 factor, a gene encoding the σ54 factor was absent from the genome sequence of M. smegmatis strain MC2 155. These results suggest the presence of a novel regulatory system in actinomycetes, including mycobacteria. PMID:21856847

Changes in transcriptional orientation are associated with increases in evolutionary rates of enterobacterial genes

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Hsiung Chao

2011-10-01

Full Text Available Abstract Background Changes in transcriptional orientation (“CTOs” occur frequently in prokaryotic genomes. Such changes usually result from genomic inversions, which may cause a conflict between the directions of replication and transcription and an increase in mutation rate. However, CTOs do not always lead to the replication-transcription confrontation. Furthermore, CTOs may cause deleterious disruptions of operon structure and/or gene regulations. The currently existing CTOs may indicate relaxation of selection pressure. Therefore, it is of interest to investigate whether CTOs have an independent effect on the evolutionary rates of the affected genes, and whether these genes are subject to any type of selection pressure in prokaryotes. Methods Three closely related enterbacteria, Escherichia coli, Klebsiella pneumoniae and Salmonella enterica serovar Typhimurium, were selected for comparisons of synonymous (dS and nonsynonymous (dN substitution rate between the genes that have experienced changes in transcriptional orientation (changed-orientation genes, “COGs” and those that do not (same-orientation genes, “SOGs”. The dN/dS ratio was also derived to evaluate the selection pressure on the analyzed genes. Confounding factors in the estimation of evolutionary rates, such as gene essentiality, gene expression level, replication-transcription confrontation, and decreased dS at gene terminals were controlled in the COG-SOG comparisons. Results We demonstrate that COGs have significantly higher dN and dS than SOGs when a series of confounding factors are controlled. However, the dN/dS ratios are similar between the two gene groups, suggesting that the increase in dS can sufficiently explain the increase in dN in COGs. Therefore, the increases in evolutionary rates in COGs may be mainly mutation-driven. Conclusions Here we show that CTOs can increase the evolutionary rates of the affected genes. This effect is independent of the

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

Directory of Open Access Journals (Sweden)

Sura Zaki Alrashid

2018-02-01

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

Science Teaching Orientations and Technology-Enhanced Tools for Student Learning

Science.gov (United States)

Campbell, Todd; Longhurst, Max; Duffy, Aaron M.; Wolf, Paul G.; Shelton, Brett E.

2013-01-01

This qualitative study examines teacher orientations and technology-enhanced tools for student learning within a science literacy framework. Data for this study came from a group of 10 eighth grade science teachers. Each of these teachers was a participant in a professional development (PD) project focused on reformed and technology-enhanced…

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

Science.gov (United States)

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

2016-09-01

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

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

Science.gov (United States)

Ehrlich, Kenneth C; Mack, Brian M

2014-06-23

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

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

Science.gov (United States)

2014-01-01

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

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

Science.gov (United States)

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

1980-01-01

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

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

Science.gov (United States)

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Intervene: a tool for intersection and visualization of multiple gene or genomic region sets.

Science.gov (United States)

Khan, Aziz; Mathelier, Anthony

2017-05-31

A common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets. Intervene and its web application companion provide an easy command line and an interactive web interface to compute intersections of multiple genomic and list sets. They have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene , with the web application available at https://asntech.shinyapps.io/intervene .

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

Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium

Directory of Open Access Journals (Sweden)

Koen Hoogendoorn

2018-06-01

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

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

DEFF Research Database (Denmark)

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

2006-01-01

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

An observation tool for studying patient-oriented workflow in hospital emergency departments.

Science.gov (United States)

Ozkaynak, M; Brennan, P

2013-01-01

Studying workflow is a critical step in designing, implementing and evaluating informatics interventions in complex sociotechnical settings, such as hospital emergency departments (EDs). Known approaches to studying workflow in clinical settings attend to the activities of individual clinicians, thus being inadequate to characterize patient care as a cooperative work. The purpose of this paper is twofold. First, we introduce a novel, theory-driven patient-oriented workflow methodology, which better addresses the complex, multiple-provider nature of patient care. Second, we report the development of an observational tool and protocol for use in studies of this type, and the results of an evaluation study. We created a tablet computer implementation of an instrument to efficiently capture patient-oriented workflow, and evaluated it through a field study in three EDs. We focused on activities occurring over time during a single patient care episode as well as the roles of the ED staff members who conducted the activities. The evidence generated supports the validity, viability, and reliability of the tool. The coverage of the tool in terms of activities and roles was satisfactory. The tool was able to capture the sequence of activity-role pairs for 108 patient care episodes. The inter-rater reliability assessment yielded a high kappa value (0.79). The patient-oriented workflow methodology has the potential to facilitate modeling patient care in EDs by characterizing both roles and activities in sequence. The methodology also provides researchers and practitioners a more realistic and comprehensive workflow perspective that can inform the design, implementation and evaluation of health information technology interventions.

Computational Tools and Algorithms for Designing Customized Synthetic Genes

Energy Technology Data Exchange (ETDEWEB)

Gould, Nathan [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States); Hendy, Oliver [Department of Biology, The College of New Jersey, Ewing, NJ (United States); Papamichail, Dimitris, E-mail: papamicd@tcnj.edu [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States)

2014-10-06

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.

Computational Tools and Algorithms for Designing Customized Synthetic Genes

International Nuclear Information System (INIS)

Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris

2014-01-01

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.

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

Directory of Open Access Journals (Sweden)

Hong Lu

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

OLYMPUS: an automated hybrid clustering method in time series gene expression. Case study: host response after Influenza A (H1N1) infection.

Science.gov (United States)

Dimitrakopoulou, Konstantina; Vrahatis, Aristidis G; Wilk, Esther; Tsakalidis, Athanasios K; Bezerianos, Anastasios

2013-09-01

The increasing flow of short time series microarray experiments for the study of dynamic cellular processes poses the need for efficient clustering tools. These tools must deal with three primary issues: first, to consider the multi-functionality of genes; second, to evaluate the similarity of the relative change of amplitude in the time domain rather than the absolute values; third, to cope with the constraints of conventional clustering algorithms such as the assignment of the appropriate cluster number. To address these, we propose OLYMPUS, a novel unsupervised clustering algorithm that integrates Differential Evolution (DE) method into Fuzzy Short Time Series (FSTS) algorithm with the scope to utilize efficiently the information of population of the first and enhance the performance of the latter. Our hybrid approach provides sets of genes that enable the deciphering of distinct phases in dynamic cellular processes. We proved the efficiency of OLYMPUS on synthetic as well as on experimental data. The discriminative power of OLYMPUS provided clusters, which refined the so far perspective of the dynamics of host response mechanisms to Influenza A (H1N1). Our kinetic model sets a timeline for several pathways and cell populations, implicated to participate in host response; yet no timeline was assigned to them (e.g. cell cycle, homeostasis). Regarding the activity of B cells, our approach revealed that some antibody-related mechanisms remain activated until day 60 post infection. The Matlab codes for implementing OLYMPUS, as well as example datasets, are freely accessible via the Web (http://biosignal.med.upatras.gr/wordpress/biosignal/). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

Tool Support for Collaborative Teaching and Learning of Object-Oriented Modelling

DEFF Research Database (Denmark)

Hansen, Klaus Marius; Ratzer, Anne Vinter

2002-01-01

Modeling is central to doing and learning object-oriented development. We present a new tool, Ideogramic UML, for gesture-based collaborative modeling with the Unified Modeling Language (UML), which can be used to collaboratively teach and learn modeling. Furthermore, we discuss how we have...

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

OpenAIRE

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

2018-01-01

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

Embedded Systems Development Tools: A MODUS-oriented Market Overview

Directory of Open Access Journals (Sweden)

Loupis Michalis

2014-03-01

Full Text Available Background: The embedded systems technology has perhaps been the most dominating technology in high-tech industries, in the past decade. The industry has correctly identified the potential of this technology and has put its efforts into exploring its full potential. Objectives: The goal of the paper is to explore the versatility of the application in the embedded system development based on one FP7-SME project. Methods/Approach: Embedded applications normally demand high resilience and quality, as well as conformity to quality standards and rigid performance. As a result embedded system developers have adopted software methods that yield high quality. The qualitative approach to examining embedded systems development tools has been applied in this work. Results: This paper presents a MODUS-oriented market analysis in the domains of Formal Verification tools, HW/SW co-simulation tools, Software Performance Optimization tools and Code Generation tools. Conclusions: The versatility of applications this technology serves is amazing. With all this performance potential, the technology has carried with itself a large number of issues which the industry essentially needs to resolve to be able to harness the full potential contained. The MODUS project toolset addressed four discrete domains of the ESD Software Market, in which corresponding open tools were developed

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

Science.gov (United States)

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

2008-01-01

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

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

Science.gov (United States)

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

2018-04-23

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

Computational Tools and Algorithms for Designing Customized Synthetic Genes

Directory of Open Access Journals (Sweden)

Nathan eGould

2014-10-01

Full Text Available Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de-novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.

CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.

Science.gov (United States)

Kartasalo, Kimmo; Pölönen, Risto-Pekka; Ojala, Marisa; Rasku, Jyrki; Lekkala, Jukka; Aalto-Setälä, Katriina; Kallio, Pasi

2015-10-26

Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structures is often limited to qualitative evaluation by human experts, hampering the throughput, repeatability and reliability of the analyses. Software tools are not readily available for this purpose and the existing methods typically rely at least partly on manual operation. We developed CytoSpectre, an automated tool based on spectral analysis, allowing the quantification of orientation and also size distributions of structures in microscopy images. CytoSpectre utilizes the Fourier transform to estimate the power spectrum of an image and based on the spectrum, computes parameter values describing, among others, the mean orientation, isotropy and size of target structures. The analysis can be further tuned to focus on targets of particular size at cellular or subcellular scales. The software can be operated via a graphical user interface without any programming expertise. We analyzed the performance of CytoSpectre by extensive simulations using artificial images, by benchmarking against FibrilTool and by comparisons with manual measurements performed for real images by a panel of human experts. The software was found to be tolerant against noise and blurring and superior to FibrilTool when analyzing realistic targets with degraded image quality. The analysis of real images indicated general good agreement between computational and manual results while also revealing notable expert-to-expert variation. Moreover, the experiment showed that CytoSpectre can handle images obtained of different cell types using different microscopy techniques. Finally, we studied the effect of mechanical stretching on cardiomyocytes to demonstrate the software in an actual experiment and observed changes in cellular orientation in response to stretching. CytoSpectre, a versatile, easy

Reliability Oriented Design Tool For the New Generation of Grid Connected PV-Inverters

DEFF Research Database (Denmark)

Sintamarean, Nicolae Cristian; Blaabjerg, Frede; Wang, Huai

2015-01-01

is achieved and is further used as an input to the lifetime model. The proposed reliability-oriented design tool is used to study the impact of mission profile (MP) variation and device degradation (aging) in the PV inverter lifetime. The obtained results indicate that the MP of the field where the PV...... inverter is operating has an important impact (up to 70%) on the converter lifetime expectation, and it should be considered in the design stage to better optimize the converter design margin. In order to have correct lifetime estimation, it is crucial to consider also the device degradation feedback (in......This paper introduces a reliability-oriented design tool for a new generation of grid-connected photovoltaic (PV) inverters. The proposed design tool consists of a real field mission profile (RFMP) model (for two operating regions: USA and Denmark), a PV panel model, a grid-connected PV inverter...

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

OpenAIRE

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

2015-01-01

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

Mouse Nkrp1-Clr gene cluster sequence and expression analyses reveal conservation of tissue-specific MHC-independent immunosurveillance.

Directory of Open Access Journals (Sweden)

Qiang Zhang

Full Text Available The Nkrp1 (Klrb1-Clr (Clec2 genes encode a receptor-ligand system utilized by NK cells as an MHC-independent immunosurveillance strategy for innate immune responses. The related Ly49 family of MHC-I receptors displays extreme allelic polymorphism and haplotype plasticity. In contrast, previous BAC-mapping and aCGH studies in the mouse suggest the neighboring and related Nkrp1-Clr cluster is evolutionarily stable. To definitively compare the relative evolutionary rate of Nkrp1-Clr vs. Ly49 gene clusters, the Nkrp1-Clr gene clusters from two Ly49 haplotype-disparate inbred mouse strains, BALB/c and 129S6, were sequenced. Both Nkrp1-Clr gene cluster sequences are highly similar to the C57BL/6 reference sequence, displaying the same gene numbers and order, complete pseudogenes, and gene fragments. The Nkrp1-Clr clusters contain a strikingly dissimilar proportion of repetitive elements compared to the Ly49 clusters, suggesting that certain elements may be partly responsible for the highly disparate Ly49 vs. Nkrp1 evolutionary rate. Focused allelic polymorphisms were found within the Nkrp1b/d (Klrb1b, Nkrp1c (Klrb1c, and Clr-c (Clec2f genes, suggestive of possible immune selection. Cell-type specific transcription of Nkrp1-Clr genes in a large panel of tissues/organs was determined. Clr-b (Clec2d and Clr-g (Clec2i showed wide expression, while other Clr genes showed more tissue-specific expression patterns. In situ hybridization revealed specific expression of various members of the Clr family in leukocytes/hematopoietic cells of immune organs, various tissue-restricted epithelial cells (including intestinal, kidney tubular, lung, and corneal progenitor epithelial cells, as well as myocytes. In summary, the Nkrp1-Clr gene cluster appears to evolve more slowly relative to the related Ly49 cluster, and likely regulates innate immunosurveillance in a tissue-specific manner.

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

Science.gov (United States)

2013-01-01

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

Patient-oriented interactive E-health tools on U.S. hospital Web sites.

Science.gov (United States)

Huang, Edgar; Chang, Chiu-Chi Angela

2012-01-01

The purpose of this study is to provide evidence for strategic planning regarding e-health development in U.S. hospitals. A content analysis of a representative sample of the U.S. hospital Web sites has revealed how U.S. hospitals have taken advantage of the 21 patient-oriented interactive tools identified in this study. Significant gaps between various types of hospitals have also been found. It is concluded that although the majority of the U.S. hospitals have adopted traditional functional tools, they need to make significant inroad in implementing the core e-business tools to serve their patients/users, making their Web sites more efficient marketing tools.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

Science.gov (United States)

Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

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

Directory of Open Access Journals (Sweden)

Junchao Liang

2016-07-01

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

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

Directory of Open Access Journals (Sweden)

M. Vahedi

2008-02-01

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

A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

Science.gov (United States)

Nowrousian, Minou

2009-04-01

During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

The ergot alkaloid gene cluster: Functional analyses and evolutionary aspects

Czech Academy of Sciences Publication Activity Database

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

2009-01-01

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

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....

Formation of stable products from cluster-cluster collisions

International Nuclear Information System (INIS)

Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

2007-01-01

The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

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

Science.gov (United States)

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

2016-03-14

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

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

Directory of Open Access Journals (Sweden)

Lee Yun-Shien

2008-03-01

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

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

Science.gov (United States)

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

2000-01-01

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

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...

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

Science.gov (United States)

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

2013-07-01

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

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

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Woods Donald E

2009-12-01

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

Histone and ribosomal RNA repetitive gene clusters of the boll weevil are linked in a tandem array.

Science.gov (United States)

Roehrdanz, R; Heilmann, L; Senechal, P; Sears, S; Evenson, P

2010-08-01

Histones are the major protein component of chromatin structure. The histone family is made up of a quintet of proteins, four core histones (H2A, H2B, H3 & H4) and the linker histones (H1). Spacers are found between the coding regions. Among insects this quintet of genes is usually clustered and the clusters are tandemly repeated. Ribosomal DNA contains a cluster of the rRNA sequences 18S, 5.8S and 28S. The rRNA genes are separated by the spacers ITS1, ITS2 and IGS. This cluster is also tandemly repeated. We found that the ribosomal RNA repeat unit of at least two species of Anthonomine weevils, Anthonomus grandis and Anthonomus texanus (Coleoptera: Curculionidae), is interspersed with a block containing the histone gene quintet. The histone genes are situated between the rRNA 18S and 28S genes in what is known as the intergenic spacer region (IGS). The complete reiterated Anthonomus grandis histone-ribosomal sequence is 16,248 bp.

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

Indian Academy of Sciences (India)

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

ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

DEFF Research Database (Denmark)

Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

2017-01-01

, e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

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

Science.gov (United States)

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

2017-01-10

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

Genome-wide association study identifies the SERPINB gene cluster as a susceptibility locus for food allergy.

Science.gov (United States)

Marenholz, Ingo; Grosche, Sarah; Kalb, Birgit; Rüschendorf, Franz; Blümchen, Katharina; Schlags, Rupert; Harandi, Neda; Price, Mareike; Hansen, Gesine; Seidenberg, Jürgen; Röblitz, Holger; Yürek, Songül; Tschirner, Sebastian; Hong, Xiumei; Wang, Xiaobin; Homuth, Georg; Schmidt, Carsten O; Nöthen, Markus M; Hübner, Norbert; Niggemann, Bodo; Beyer, Kirsten; Lee, Young-Ae

2017-10-20

Genetic factors and mechanisms underlying food allergy are largely unknown. Due to heterogeneity of symptoms a reliable diagnosis is often difficult to make. Here, we report a genome-wide association study on food allergy diagnosed by oral food challenge in 497 cases and 2387 controls. We identify five loci at genome-wide significance, the clade B serpin (SERPINB) gene cluster at 18q21.3, the cytokine gene cluster at 5q31.1, the filaggrin gene, the C11orf30/LRRC32 locus, and the human leukocyte antigen (HLA) region. Stratifying the results for the causative food demonstrates that association of the HLA locus is peanut allergy-specific whereas the other four loci increase the risk for any food allergy. Variants in the SERPINB gene cluster are associated with SERPINB10 expression in leukocytes. Moreover, SERPINB genes are highly expressed in the esophagus. All identified loci are involved in immunological regulation or epithelial barrier function, emphasizing the role of both mechanisms in food allergy.

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

Science.gov (United States)

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

2018-01-01

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

Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization

Directory of Open Access Journals (Sweden)

Ronaldo Pornillosa Parreno Jr

2015-08-01

Full Text Available Abstract In this study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with electricity. The algorithm provided adifferent approach in clustering problem which combines conceptual and distance-based clustering algorithmsto analyze potential clusters using spanning tree with the shortest possible edge weight and creating final cluster trees based on the test of inconsistency for the edges. The clustering criteria consists of commonly used distance measure with the addition of household information as basis for the ability to pay ATP value. The combination of these two parameters resulted to a more significant and realistic clusters since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings of households. In addition the implications of varying geographical features were incorporated in the algorithm by using routing index across the locations of the households. This new approach of connecting the households in an area was applied in an actual case study of one village or barangay that was not yet energized. The results of clustering algorithm generated cluster trees which could becomethetheoretical basis for power utilities to plan the initial network arrangement of electrification. Scenario analysis conducted on the two strategies of clustering the households provideddifferent alternatives for the optimization of the cost of electrification. Futhermorethe benefits associated with the two strategies formulated from the two scenarios was evaluated using benefit cost ratio BC to determine which is more economically advantageous. The results of the study showed that clustering algorithm proved to be effective in solving electrification optimization problem and serves its purpose as a planning support tool which can facilitate electrification in rural areas and achieve cost-effectiveness.

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

Directory of Open Access Journals (Sweden)

Chapuisat Michel

2009-03-01

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

Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

OpenAIRE

Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

2014-01-01

Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of ...

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

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

Science.gov (United States)

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

Tools of integration of innovation-oriented machine-building enterprises in industrial park environment

Directory of Open Access Journals (Sweden)

К.О. Boiarynova

2017-08-01

Full Text Available The research is devoted to the development of the tools for the integration of innovation-oriented mechanical engineering enterprises into the environment of industrial park as functional economic systems, which are capable on the own development basis to provide the development of resident enterprises. The article analyzes the opportunities for the development of mechanical engineering enterprises. The formed structure of the mechanism of integration of mechanical engineering enterprises as functional economic systems into the industrial park environment is based on: 1 the development of participation programs in the industrial park of the mechanical engineering enterprises as an innovation-oriented partner, which foresees the development of the enterprise immediately and the development of other residents; 2 the provision of high-tech equipment of resident enterprises of industrial parks; 3 the creation of subsidiary-spin-out enterprises of large mechanical engineering enterprises for high-tech production in the industrial park. The author proposes the road map that reveals the procedures for the integration and functioning the investigated enterprises through interaction as well as in the ecosystem of the industrial park and in the general ecosystem of functioning, and the tools for providing economic functionality through economic and organizational proceedings at preventive, partner and resident phases of integration. The tools allow the innovation-oriented mechanical engineering enterprises to integrate into such territorial structures as industrial parks, this in complex will allow carrying out their purposes in the development of the real sector of the economy.

Design tool for offshore wind farm cluster planning

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Madsen, Peter Hauge; Giebel, Gregor

2015-01-01

In the framework of the FP7 project EERA DTOC: Design Tool for Offshore wind farm Cluster, a new software supporting the planning of offshore wind farms was developed, based on state-of-the-art approaches from large scale wind potential to economic benchmarking. The model portfolio includes WAs......P, FUGA, WRF, Net-Op, LCoE model, CorWind, FarmFlow, EeFarm and grid code compliance calculations. The development is done by members from European Energy Research Alliance (EERA) and guided by several industrial partners. A commercial spin-off from the project is the tool ‘Wind & Economy’. The software...... by the software and several tests were performed. The calculations include the smoothing effect on produced energy between wind farms located in different regional wind zones and the short time scales relevant for assessing balancing power. The grid code compliance was tested for several cases and the results...

Design tool for offshore wind farm clusters

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Giebel, Gregor; Waldl, Igor

2015-01-01

. The software includes wind farm wake models, energy yield models, inter-array and long cable and grid component models, grid code compliance and ancillary services models. The common score for evaluation in order to compare different layouts is levelized cost of energy (LCoE). The integrated DTOC software...... Research Alliance (EERA) and a number of industrial partners. The approach has been to develop a robust, efficient, easy to use and flexible tool, which integrates software relevant for planning offshore wind farms and wind farm clusters and supports the user with a clear optimization work flow...... is developed within the project using open interface standards and is now available as the commercial software product Wind&Economy....

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

Directory of Open Access Journals (Sweden)

Emily J. Parker

2013-08-01

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

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.

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

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Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an

GraphCrunch 2: Software tool for network modeling, alignment and clustering

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Hayes Wayne

2011-01-01

Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other

Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

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Sharma Animesh

2007-01-01

Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

Genome-Wide Analysis of Secondary Metabolite Gene Clusters in Ophiostoma ulmi and Ophiostoma novo-ulmi Reveals a Fujikurin-Like Gene Cluster with a Putative Role in Infection

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Nicolau Sbaraini

2017-06-01

Full Text Available The emergence of new microbial pathogens can result in destructive outbreaks, since their hosts have limited resistance and pathogens may be excessively aggressive. Described as the major ecological incident of the twentieth century, Dutch elm disease, caused by ascomycete fungi from the Ophiostoma genus, has caused a significant decline in elm tree populations (Ulmus sp. in North America and Europe. Genome sequencing of the two main causative agents of Dutch elm disease (Ophiostoma ulmi and Ophiostoma novo-ulmi, along with closely related species with different lifestyles, allows for unique comparisons to be made to identify how pathogens and virulence determinants have emerged. Among several established virulence determinants, secondary metabolites (SMs have been suggested to play significant roles during phytopathogen infection. Interestingly, the secondary metabolism of Dutch elm pathogens remains almost unexplored, and little is known about how SM biosynthetic genes are organized in these species. To better understand the metabolic potential of O. ulmi and O. novo-ulmi, we performed a deep survey and description of SM biosynthetic gene clusters (BGCs in these species and assessed their conservation among eight species from the Ophiostomataceae family. Among 19 identified BGCs, a fujikurin-like gene cluster (OpPKS8 was unique to Dutch elm pathogens. Phylogenetic analysis revealed that orthologs for this gene cluster are widespread among phytopathogens and plant-associated fungi, suggesting that OpPKS8 may have been horizontally acquired by the Ophiostoma genus. Moreover, the detailed identification of several BGCs paves the way for future in-depth research and supports the potential impact of secondary metabolism on Ophiostoma genus’ lifestyle.

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

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

2007-10-01

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

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

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Jine Li

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

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

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

2015-02-01

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

Gravitation field algorithm and its application in gene cluster

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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.

Developing Programming Tools to Handle Traveling Salesman Problem by the Three Object-Oriented Languages

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Hassan Ismkhan

2014-01-01

Full Text Available The traveling salesman problem (TSP is one of the most famous problems. Many applications and programming tools have been developed to handle TSP. However, it seems to be essential to provide easy programming tools according to state-of-the-art algorithms. Therefore, we have collected and programmed new easy tools by the three object-oriented languages. In this paper, we present ADT (abstract data type of developed tools at first; then we analyze their performance by experiments. We also design a hybrid genetic algorithm (HGA by developed tools. Experimental results show that the proposed HGA is comparable with the recent state-of-the-art applications.

Draft genome sequence of Streptomyces coelicoflavus ZG0656 reveals the putative biosynthetic gene cluster of acarviostatin family α-amylase inhibitors.

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Guo, X; Geng, P; Bai, F; Bai, G; Sun, T; Li, X; Shi, L; Zhong, Q

2012-08-01

The aims of this study are to obtain the draft genome sequence of Streptomyces coelicoflavus ZG0656, which produces novel acarviostatin family α-amylase inhibitors, and then to reveal the putative acarviostatin-related gene cluster and the biosynthetic pathway. The draft genome sequence of S. coelicoflavus ZG0656 was generated using a shotgun approach employing a combination of 454 and Solexa sequencing technologies. Genome analysis revealed a putative gene cluster for acarviostatin biosynthesis, termed sct-cluster. The cluster contains 13 acarviostatin synthetic genes, six transporter genes, four starch degrading or transglycosylation enzyme genes and two regulator genes. On the basis of bioinformatic analysis, we proposed a putative biosynthetic pathway of acarviostatins. The intracellular steps produce a structural core, acarviostatin I00-7-P, and the extracellular assemblies lead to diverse acarviostatin end products. The draft genome sequence of S. coelicoflavus ZG0656 revealed the putative biosynthetic gene cluster of acarviostatins and a putative pathway of acarviostatin production. To our knowledge, S. coelicoflavus ZG0656 is the first strain in this species for which a genome sequence has been reported. The analysis of sct-cluster provided important insights into the biosynthesis of acarviostatins. This work will be a platform for producing novel variants and yield improvement. © 2012 The Authors. Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

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

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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.

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

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

1993-01-01

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

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

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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.

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

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

2016-05-01

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

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

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

2006-01-01

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

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

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

2008-08-12

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

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

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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

Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

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Crnovčić, Ivana; Rückert, Christian; Semsary, Siamak; Lang, Manuel; Kalinowski, Jörn; Keller, Ullrich

2017-01-01

Sequencing the actinomycin (acm) biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X), revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm biosynthetic gene clusters lack a kynurenine-3-monooxygenase gene necessary for biosynthesis of 3-hydroxy-4-methylanthranilic acid, the building block of the Acm chromophore, which suggests participation of a genome-encoded relevant monooxygenase during Acm biosynthesis in both S. chrysomallus and S

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

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Michelle Carey

2016-10-01

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

Object-Oriented Software Tools for the Construction of Preconditioners

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Eva Mossberg

1997-01-01

Full Text Available In recent years, there has been considerable progress concerning preconditioned iterative methods for large and sparse systems of equations arising from the discretization of differential equations. Such methods are particularly attractive in the context of high-performance (parallel computers. However, the implementation of a preconditioner is a nontrivial task. The focus of the present contribution is on a set of object-oriented software tools that support the construction of a family of preconditioners based on fast transforms. By combining objects of different classes, it is possible to conveniently construct any preconditioner within this family.

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

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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.

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

Science.gov (United States)

Shahbaba, Babak; Johnson, Wesley O

2013-05-30

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

Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

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Crnovčić I

2017-04-01

Full Text Available Ivana Crnovčić,1 Christian Rückert,2 Siamak Semsary,1 Manuel Lang,1 Jörn Kalinowski,2 Ullrich Keller1 1Institut für Chemie, Technische Universität Berlin, Berlin-Charlottenburg, 2Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany Abstract: Sequencing the actinomycin (acm biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X, revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Comprehensive cluster analysis with Transitivity Clustering.

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Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

2011-03-01

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

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

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Dian Anggraini Suroto

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

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

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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.

The person-oriented approach: A short theoretical and practical guide

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Lars R. Bergman

2014-05-01

Full Text Available A short overview of the person-oriented approach is given as a guide to the researcher interested in carrying out person-oriented research. Theoretical, methodological, and practical considerations of the approach are discussed. First, some historical roots are traced, followed by a description of the holisticinteractionistic research paradigm, which provided the general framework for the development of the modern person-oriented approach. The approach has both a theoretical and a methodological facet and after presenting its key theoretical tenets, an overview is given of some common person-oriented methods. Central to the person-oriented approach is a system view with its components together forming a pattern regarded as indivisible. This pattern should be understood and studied as a whole, not broken up into pieces (variables that are studied as separate entities. Hence, usually methodological tools are used by which whole patterns are analysed (e.g. cluster analysis. An empirical example is given where the pattern development of school grades is studied.

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

Science.gov (United States)

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

2018-06-15

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

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

Science.gov (United States)

Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

GO(vis), a gene ontology visualization tool based on multi-dimensional values.

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Ning, Zi; Jiang, Zhenran

2010-05-01

Most of gene product similarity measurements concentrate on the information content of Gene Ontology (GO) terms or use a path-based similarity between GO terms, which may ignore other important information contained in the structure of the ontology. In our study, we integrate different GO similarity measure approaches to analyze the functional relationship of genes and gene products with a new triangle-based visualization tool called GO(Vis). The purpose of this tool is to demonstrate the effect of three important information factors when measuring the similarity between gene products. One advantage of this tool is that its important ratio can be adjusted to meet different measuring requirements according to the biological knowledge of each factor. The experimental results demonstrate that GO(Vis) can display diagrams of the functional relationship for gene products effectively.

Clusters of galaxies as tools in observational cosmology : results from x-ray analysis

International Nuclear Information System (INIS)

Weratschnig, J.M.

2009-01-01

Clusters of galaxies are the largest gravitationally bound structures in the universe. They can be used as ideal tools to study large scale structure formation (e.g. when studying merger clusters) and provide highly interesting environments to analyse several characteristic interaction processes (like ram pressure stripping of galaxies, magnetic fields). In this dissertation thesis, we have studied several clusters of galaxies using X-ray observations. To obtain scientific results, we have applied different data reduction and analysis methods. With a combination of morphological and spectral analysis, the merger cluster Abell 514 was studied in much detail. It has a highly interesting morphology and shows signs for an ongoing merger as well as a shock. using a new method to detect substructure, we have analysed several clusters to determine whether any substructure is present in the X-ray image. This hints towards a real structure in the distribution of the intra-cluster medium (ICM) and is evidence for ongoing mergers. The results from this analysis are extensively used with the cluster of galaxies Abell S1136. Here, we study the ICM distribution and compare its structure with the spatial distribution of star forming galaxies. Cluster magnetic fields are another important topic of my thesis. They can be studied in Radio observations, which can be put into relation with results from X-ray observations. using observational data from several clusters, we could support the theory that cluster magnetic fields are frozen into the ICM. (author)

The capacity limitations of orientation summary statistics

Science.gov (United States)

Attarha, Mouna; Moore, Cathleen M.

2015-01-01

The simultaneous–sequential method was used to test the processing capacity of establishing mean orientation summaries. Four clusters of oriented Gabor patches were presented in the peripheral visual field. One of the clusters had a mean orientation that was tilted either left or right while the mean orientations of the other three clusters were roughly vertical. All four clusters were presented at the same time in the simultaneous condition whereas the clusters appeared in temporal subsets of two in the sequential condition. Performance was lower when the means of all four clusters had to be processed concurrently than when only two had to be processed in the same amount of time. The advantage for establishing fewer summaries at a given time indicates that the processing of mean orientation engages limited-capacity processes (Experiment 1). This limitation cannot be attributed to crowding, low target-distractor discriminability, or a limited-capacity comparison process (Experiments 2 and 3). In contrast to the limitations of establishing multiple summary representations, establishing a single summary representation unfolds without interference (Experiment 4). When interpreted in the context of recent work on the capacity of summary statistics, these findings encourage reevaluation of the view that early visual perception consists of summary statistic representations that unfold independently across multiple areas of the visual field. PMID:25810160

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Energy Technology Data Exchange (ETDEWEB)

Yoo, Wucherl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koo, Michelle [Univ. of California, Berkeley, CA (United States); Cao, Yu [California Inst. of Technology (CalTech), Pasadena, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-09-17

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

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...

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

Science.gov (United States)

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

2012-01-01

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

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

Science.gov (United States)

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics

Peac – A set of tools to quickly enable Proof on a cluster

International Nuclear Information System (INIS)

Ganis, G; Vala, M

2012-01-01

With advent of the analysis phase of Lhcdata-processing, interest in Proof technology has considerably increased. While setting up a simple Proof cluster for basic usage is reasonably straightforward, exploiting the several new functionalities added in recent times may be complicated. Peac, standing for Proof Enabled Analysis Cluster, is a set of tools aiming to facilitate the setup and management of a Proof cluster. Peac is based on the experience made by setting up Proof for the Alice analysis facilities. It allows to easily build and configure Root and the additional software needed on the cluster, and may serve as distributor of binaries via Xrootd. Peac uses Proof-On-Demand (PoD) for resource management (start, stop or daemons). Finally, Peac sets-up and configures dataset management (using the Afdsmgrd daemon), as well as cluster monitoring (machine status and Proof query summaries) using MonAlisa. In this respect, a MonAlisa page has been dedicated to Peac users, so that a cluster managed by Peac can be automatically monitored. In this paper we present and describe the status and main components of Peac and show details about its usage.

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

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2008-07-01

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

New tools in regenerative medicine: gene therapy.

Science.gov (United States)

Muñoz Ruiz, Miguel; Regueiro, José R

2012-01-01

Gene therapy aims to transfer genetic material into cells to provide them with new functions. A gene transfer agent has to be safe, capable of expressing the desired gene for a sustained period of time in a sufficiently large population of cells to produce a biological effect. Identifying a gene transfer tool that meets all of these criteria has proven to be a difficult objective. Viral and nonviral vectors, in vivo, ex vivo and in situ strategies co-exist at present, although ex vivo lenti-or retroviral vectors are presently the most popular.Natural stem cells (from embryonic, hematopoietic, mesenchymal, or adult tissues) or induced progenitor stem (iPS) cells can be modified by gene therapy for use in regenerative medicine. Among them, hematopoietic stem cells have shown clear clinical benefit, but iPS cells hold humongous potential with no ethical concerns.

Characterization, expression, and mutation of the Lactococcus lactis galPMKTE genes, involved in galactose utilization via the Leloir pathway

NARCIS (Netherlands)

Groossiord, B.P.; Luesink, E.J.; Vaughan, E.E.; Arnaud, A.; Vos, de W.M.

2003-01-01

A cluster containing five similarly oriented genes involved in the metabolism of galactose via the Leloir pathway in Lactococcus lactis subsp. cremoris MG1363 was cloned and characterized. The order of the genes is galPMKTE, and these genes encode a galactose permease (GalP), an aldose I-epimerase

Human major histocompatibility complex contains a minimum of 19 genes between the complement cluster and HLA-B

International Nuclear Information System (INIS)

Spies, T.; Bresnahan, M.; Strominger, J.L.

1989-01-01

A 600-kilobase (kb) DNA segment from the human major histocompatibility complex (MHC) class III region was isolated by extension of a previous 435-kb chromosome walk. The contiguous series of cloned overlapping cosmids contains the entire 555-kb interval between C2 in the complement gene cluster and HLA-B. This region is known to encode the tumor necrosis factors (TNFs) α and β, B144, and the major heat shock protein HSP70. Moreover, a cluster of genes, BAT1-BAT5 (HLA-B-associated transcripts) have been localized in the vicinity of the genes for TNFα and TNFβ. An additional four genes were identified by isolation of corresponding cDNA clones with cosmid DNA probes. These genes for BAT6-BAT9 were mapped near the gene for C2 within a 120-kb region that includes a HSP70 gene pair. These results, together with complementary data from a similar recent study, indicated the presence of a minimum of 19 genes within the C2-HLA-B interval of the MHC class III region. Although the functional properties of most of these genes are yet unknown, they may be involved in some aspects of immunity. This idea is supported by the genetic mapping of the hematopoietic histocompatibility locus-1 (Hh-1) in recombinant mice between TNFα and H-2S, which is homologous to the complement gene cluster in humans

Topological clustering as a tool for planning water quality monitoring in water distribution networks

DEFF Research Database (Denmark)

Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

2015-01-01

) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

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.

Genomic characterization of a new endophytic Streptomyces kebangsaanensis identifies biosynthetic pathway gene clusters for novel phenazine antibiotic production

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Juwairiah Remali

2017-11-01

Full Text Available Background Streptomyces are well known for their capability to produce many bioactive secondary metabolites with medical and industrial importance. Here we report a novel bioactive phenazine compound, 6-((2-hydroxy-4-methoxyphenoxy carbonyl phenazine-1-carboxylic acid (HCPCA extracted from Streptomyces kebangsaanensis, an endophyte isolated from the ethnomedicinal Portulaca oleracea. Methods The HCPCA chemical structure was determined using nuclear magnetic resonance spectroscopy. We conducted whole genome sequencing for the identification of the gene cluster(s believed to be responsible for phenazine biosynthesis in order to map its corresponding pathway, in addition to bioinformatics analysis to assess the potential of S. kebangsaanensis in producing other useful secondary metabolites. Results The S. kebangsaanensis genome comprises an 8,328,719 bp linear chromosome with high GC content (71.35% consisting of 12 rRNA operons, 81 tRNA, and 7,558 protein coding genes. We identified 24 gene clusters involved in polyketide, nonribosomal peptide, terpene, bacteriocin, and siderophore biosynthesis, as well as a gene cluster predicted to be responsible for phenazine biosynthesis. Discussion The HCPCA phenazine structure was hypothesized to derive from the combination of two biosynthetic pathways, phenazine-1,6-dicarboxylic acid and 4-methoxybenzene-1,2-diol, originated from the shikimic acid pathway. The identification of a biosynthesis pathway gene cluster for phenazine antibiotics might facilitate future genetic engineering design of new synthetic phenazine antibiotics. Additionally, these findings confirm the potential of S. kebangsaanensis for producing various antibiotics and secondary metabolites.

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

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Morten Thrane Nielsen

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

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

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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.

AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

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Xia Yuannan

2006-12-01

Full Text Available Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressed genes. Results AffyMiner is a tool developed for detecting differentially expressed genes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications. Conclusion AffyMiner fills an important gap in finding differentially expressed genes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

Contribution of the Pmra Promoter to Expression of Genes in the Escherichia coli mra Cluster of Cell Envelope Biosynthesis and Cell Division Genes

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Mengin-Lecreulx, Dominique; Ayala, Juan; Bouhss, Ahmed; van Heijenoort, Jean; Parquet, Claudine; Hara, Hiroshi

1998-01-01

Recently, a promoter for the essential gene ftsI, which encodes penicillin-binding protein 3 of Escherichia coli, was precisely localized 1.9 kb upstream from this gene, at the beginning of the mra cluster of cell division and cell envelope biosynthesis genes (H. Hara, S. Yasuda, K. Horiuchi, and J. T. Park, J. Bacteriol. 179:5802–5811, 1997). Disruption of this promoter (Pmra) on the chromosome and its replacement by the lac promoter (Pmra::Plac) led to isopropyl-β-d-thiogalactopyranoside (IPTG)-dependent cells that lysed in the absence of inducer, a defect which was complemented only when the whole region from Pmra to ftsW, the fifth gene downstream from ftsI, was provided in trans on a plasmid. In the present work, the levels of various proteins involved in peptidoglycan synthesis and cell division were precisely determined in cells in which Pmra::Plac promoter expression was repressed or fully induced. It was confirmed that the Pmra promoter is required for expression of the first nine genes of the mra cluster: mraZ (orfC), mraW (orfB), ftsL (mraR), ftsI, murE, murF, mraY, murD, and ftsW. Interestingly, three- to sixfold-decreased levels of MurG and MurC enzymes were observed in uninduced Pmra::Plac cells. This was correlated with an accumulation of the nucleotide precursors UDP–N-acetylglucosamine and UDP–N-acetylmuramic acid, substrates of these enzymes, and with a depletion of the pool of UDP–N-acetylmuramyl pentapeptide, resulting in decreased cell wall peptidoglycan synthesis. Moreover, the expression of ftsZ, the penultimate gene from this cluster, was significantly reduced when Pmra expression was repressed. It was concluded that the transcription of the genes located downstream from ftsW in the mra cluster, from murG to ftsZ, is also mainly (but not exclusively) dependent on the Pmra promoter. PMID:9721276

De novo cloning and annotation of genes associated with immunity, detoxification and energy metabolism from the fat body of the oriental fruit fly, Bactrocera dorsalis.

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Wen-Jia Yang

Full Text Available The oriental fruit fly, Bactrocera dorsalis, is a destructive pest in tropical and subtropical areas. In this study, we performed transcriptome-wide analysis of the fat body of B. dorsalis and obtained more than 59 million sequencing reads, which were assembled into 27,787 unigenes with an average length of 591 bp. Among them, 17,442 (62.8% unigenes matched known proteins in the NCBI database. The assembled sequences were further annotated with gene ontology, cluster of orthologous group terms, and Kyoto encyclopedia of genes and genomes. In depth analysis was performed to identify genes putatively involved in immunity, detoxification, and energy metabolism. Many new genes were identified including serpins, peptidoglycan recognition proteins and defensins, which were potentially linked to immune defense. Many detoxification genes were identified, including cytochrome P450s, glutathione S-transferases and ATP-binding cassette (ABC transporters. Many new transcripts possibly involved in energy metabolism, including fatty acid desaturases, lipases, alpha amylases, and trehalose-6-phosphate synthases, were identified. Moreover, we randomly selected some genes to examine their expression patterns in different tissues by quantitative real-time PCR, which indicated that some genes exhibited fat body-specific expression in B. dorsalis. The identification of a numerous transcripts in the fat body of B. dorsalis laid the foundation for future studies on the functions of these genes.

A Novel Prokaryotic Green Fluorescent Protein Expression System for Testing Gene Editing Tools Activity Like Zinc Finger Nuclease.

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Sabzehei, Faezeh; Kouhpayeh, Shirin; Dastjerdeh, Mansoureh Shahbazi; Khanahmad, Hossein; Salehi, Rasoul; Naderi, Shamsi; Taghizadeh, Razieh; Rabiei, Parisa; Hejazi, Zahra; Shariati, Laleh

2017-01-01

Gene editing technology has created a revolution in the field of genome editing. The three of the most famous tools in gene editing technology are zinc finger nucleases (ZFNs), transcription activator-like effector nucleases, clustered regularly interspaced short palindromic repeats (CRISPR), and CRISPR-associated systems. As their predictable nature, it is necessary to assess their efficiency. There are some methods for this purpose, but most of them are time labor and complicated. Here, we introduce a new prokaryotic reporter system, which makes it possible to evaluate the efficiency of gene editing tools faster, cheaper, and simpler than previous methods. At first, the target sites of a custom ZFN, which is designed against a segment of ampicillin resistance gene, were cloned on both sides of green fluorescent protein (GFP) gene to construct pPRO-GFP. Then pPRO-GFP was transformed into Escherichia coli TOP10F' that contains pZFN (contains expression cassette of a ZFN against ampicillin resistant gene), or p15A-KanaR as a negative control. The transformed bacteria were cultured on three separate media that contained ampicillin, kanamycin, and ampicillin + kanamycin; then the resulted colonies were assessed by flow cytometry. The results of flow cytometry showed a significant difference between the case (bacteria contain pZFN) and control (bacteria contain p15A, KanaR) in MFI (Mean Fluorescence Intensity) ( P < 0.0001). According to ZFN efficiency, it can bind and cut the target sites, the bilateral cutting can affect the intensity of GFP fluorescence. Our flow cytometry results showed that this ZFN could reduce the intensity of GFP color and colony count of bacteria in media containing amp + kana versus control sample.

An analytical method on the surface residual stress for the cutting tool orientation

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Li, Yueen; Zhao, Jun; Wang, Wei

2010-03-01

The residual stress is measured by choosing 8 kinds orientations on cutting the H13 dies steel on the HSM in the experiment of this paper. The measured data shows on that the residual stress exists periodicity for the different rake angle (β) and side rake angle (θ) parameters, further study find that the cutting tool orientations have closed relationship with the residual stresses, and for the original of the machined residual stress on the surface from the cutting force and the axial force, it can be gained the simply model of tool-workpiece force, using the model it can be deduced the residual stress model, which is feasible to calculate the size of residual stress. And for almost all the measured residual stresses are compressed stress, the compressed stress size and the direction could be confirmed by the input data for the H13 on HSM. As the result, the residual stress model is the key for optimization of rake angle (β) and side rake angle (θ) in theory, using the theory the more cutting mechanism can be expressed.

Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering.

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Chang, Jinyuan; Zhou, Wen; Zhou, Wen-Xin; Wang, Lan

2017-03-01

Comparing large covariance matrices has important applications in modern genomics, where scientists are often interested in understanding whether relationships (e.g., dependencies or co-regulations) among a large number of genes vary between different biological states. We propose a computationally fast procedure for testing the equality of two large covariance matrices when the dimensions of the covariance matrices are much larger than the sample sizes. A distinguishing feature of the new procedure is that it imposes no structural assumptions on the unknown covariance matrices. Hence, the test is robust with respect to various complex dependence structures that frequently arise in genomics. We prove that the proposed procedure is asymptotically valid under weak moment conditions. As an interesting application, we derive a new gene clustering algorithm which shares the same nice property of avoiding restrictive structural assumptions for high-dimensional genomics data. Using an asthma gene expression dataset, we illustrate how the new test helps compare the covariance matrices of the genes across different gene sets/pathways between the disease group and the control group, and how the gene clustering algorithm provides new insights on the way gene clustering patterns differ between the two groups. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2016, The International Biometric Society.

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

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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.

TMS over the supramarginal gyrus delays selection of appropriate grasp orientation during reaching and grasping tools for use.

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McDowell, Tomás; Holmes, Nicholas P; Sunderland, Alan; Schürmann, Martin

2018-03-09

Tool use, a ubiquitous part of human behaviour, requires manipulation control and knowledge of tool purpose. Neuroimaging and neuropsychological research posit that these two processes are supported by separate brain regions, ventral premotor and inferior parietal for manipulation control, and posterior middle temporal cortex for tool knowledge, lateralised to the left hemisphere. Action plans for tool use need to integrate these two separate processes, which is likely supported by the left supramarginal gyrus (SMG). However, whether this integration occurs during action execution is not known. To clarify the role of the SMG we conducted two experiments in which healthy participants reached to grasp everyday tools with the explicit instruction to use them directly following their grasp. To study the integration of manipulation control and tool knowledge within a narrow time window we mechanically perturbed the orientation of the tool to force participants to correct grasp orientation 'on-line' during the reaching movement. In experiment 1, twenty healthy participants reached with their left hand to grasp a tool. Double-pulse transcranial magnetic stimulation (TMS) was applied, in different blocks over left or right SMG at the onset of perturbation. Kinematic data revealed delayed and erroneous online correction after TMS over left and right SMG. In Experiment 2 twelve participants reached, in different blocks, with their left or right hand and TMS was applied over SMG ipsilateral to the reaching hand. A similar effect on correction was observed for ipsilateral stimulation when reaching with the left and right hands, and no effect of or interaction with hemisphere was observed. Our findings implicate a bilateral role of the SMG in correcting movements and selection of appropriate grasp orientation during reaching to grasp tools for use. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

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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.

Creating a new innovation practice and a different innovation orientation through implementation of an idea competition tool

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Nicolajsen, Hanne Westh; Scupola, Ada

2012-01-01

We investigate how an idea competition tool act as catalyst to create a new innovation practice and innovation orientation in an engineering consultancy company. The idea competition is used internally in the organization to collect employee ideas for internal process improvements. The case study...... barriers by creating a strategic business architecture encouraging employees to contribute with innovative ideas that the company may develop and implement for the good of the company. The findings indicate that more and different innovation orientations may co-exist in the same organization, complementing...... each other, such as balancing an external customer orientation with an innovation orientation focusing on internal innovations....

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

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Wolf Yuri I

2012-12-01

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

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

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

2018-05-21

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

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

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

2004-01-01

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

A functional bikaverin biosynthesis gene cluster in rare strains of Botrytis cinerea is positively controlled by VELVET.

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Julia Schumacher

Full Text Available The gene cluster responsible for the biosynthesis of the red polyketidic pigment bikaverin has only been characterized in Fusarium ssp. so far. Recently, a highly homologous but incomplete and nonfunctional bikaverin cluster has been found in the genome of the unrelated phytopathogenic fungus Botrytis cinerea. In this study, we provided evidence that rare B. cinerea strains such as 1750 have a complete and functional cluster comprising the six genes orthologous to Fusarium fujikuroi ffbik1-ffbik6 and do produce bikaverin. Phylogenetic analysis confirmed that the whole cluster was acquired from Fusarium through a horizontal gene transfer (HGT. In the bikaverin-nonproducing strain B05.10, the genes encoding bikaverin biosynthesis enzymes are nonfunctional due to deleterious mutations (bcbik2-3 or missing (bcbik1 but interestingly, the genes encoding the regulatory proteins BcBIK4 and BcBIK5 do not harbor deleterious mutations which suggests that they may still be functional. Heterologous complementation of the F. fujikuroi Δffbik4 mutant confirmed that bcbik4 of strain B05.10 is indeed fully functional. Deletion of bcvel1 in the pink strain 1750 resulted in loss of bikaverin and overproduction of melanin indicating that the VELVET protein BcVEL1 regulates the biosynthesis of the two pigments in an opposite manner. Although strain 1750 itself expresses a truncated BcVEL1 protein (100 instead of 575 aa that is nonfunctional with regard to sclerotia formation, virulence and oxalic acid formation, it is sufficient to regulate pigment biosynthesis (bikaverin and melanin and fenhexamid HydR2 type of resistance. Finally, a genetic cross between strain 1750 and a bikaverin-nonproducing strain sensitive to fenhexamid revealed that the functional bikaverin cluster is genetically linked to the HydR2 locus.

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

OpenAIRE

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

2006-01-01

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

Functional characterization of KanP, a methyltransferase from the kanamycin biosynthetic gene cluster of Streptomyces kanamyceticus.

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Nepal, Keshav Kumar; Yoo, Jin Cheol; Sohng, Jae Kyung

2010-09-20

KanP, a putative methyltransferase, is located in the kanamycin biosynthetic gene cluster of Streptomyces kanamyceticus ATCC12853. Amino acid sequence analysis of KanP revealed the presence of S-adenosyl-L-methionine binding motifs, which are present in other O-methyltransferases. The kanP gene was expressed in Escherichia coli BL21 (DE3) to generate the E. coli KANP recombinant strain. The conversion of external quercetin to methylated quercetin in the culture extract of E. coli KANP proved the function of kanP as S-adenosyl-L-methionine-dependent methyltransferase. This is the first report concerning the identification of an O-methyltransferase gene from the kanamycin gene cluster. The resistant activity assay and RT-PCR analysis demonstrated the leeway for obtaining methylated kanamycin derivatives from the wild-type strain of kanamycin producer. 2009 Elsevier GmbH. All rights reserved.

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

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

2018-01-01

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

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

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Ian C McDowell

2018-01-01

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

Cluster magnetic field observations of the bowshock: Orientation, motion and structure

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T. S. Horbury

Full Text Available Four spacecraft Cluster magnetic field observations of the low quasi-perpendicular terrestrial bowshock are presented for the first time. Multiple quasi-perpendicular crossings on 25 December 2000 are analysed. By combining data from the four spacecraft, bowshock orientations and velocities can be calculated. It is shown that, even while in rapid motion, the bowshock normal direction remains remarkably constant, and that coplanarity estimates are accurate to, typically, around 20°. Magnetic field magnitude profiles are shown to be very well correlated between spacecraft although downstream waves with fluctuations perpendicular to the local field, while statistically similar at all four spacecraft, are poorly correlated on separation scales of several hundred km. Examples are shown of a number of bowshock phenomena, including non-standing fluctuations in the shock foot and the shock interacting with changing solar wind conditions.

Key words. Interplanetary physics (planetary bow shocks Space plasma physics (shock waves; waves and instabilities

Cluster magnetic field observations of the bowshock: Orientation, motion and structure

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T. S. Horbury

2001-09-01

Full Text Available Four spacecraft Cluster magnetic field observations of the low quasi-perpendicular terrestrial bowshock are presented for the first time. Multiple quasi-perpendicular crossings on 25 December 2000 are analysed. By combining data from the four spacecraft, bowshock orientations and velocities can be calculated. It is shown that, even while in rapid motion, the bowshock normal direction remains remarkably constant, and that coplanarity estimates are accurate to, typically, around 20°. Magnetic field magnitude profiles are shown to be very well correlated between spacecraft although downstream waves with fluctuations perpendicular to the local field, while statistically similar at all four spacecraft, are poorly correlated on separation scales of several hundred km. Examples are shown of a number of bowshock phenomena, including non-standing fluctuations in the shock foot and the shock interacting with changing solar wind conditions.Key words. Interplanetary physics (planetary bow shocks Space plasma physics (shock waves; waves and instabilities

A literature search tool for intelligent extraction of disease-associated genes.

Science.gov (United States)

Jung, Jae-Yoon; DeLuca, Todd F; Nelson, Tristan H; Wall, Dennis P

2014-01-01

To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods. We developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article. We compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder-gene link are more extensive and accurate than other general purpose gene-to-disorder association databases. We implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene-disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately.

The human TREM gene cluster at 6p21.1 encodes both activating and inhibitory single IgV domain receptors and includes NKp44.

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Allcock, Richard J N; Barrow, Alexander D; Forbes, Simon; Beck, Stephan; Trowsdale, John

2003-02-01

We have characterized a cluster of single immunoglobulin variable (IgV) domain receptors centromeric of the major histocompatibility complex (MHC) on human chromosome 6. In addition to triggering receptor expressed on myeloid cells (TREM)-1 and TREM2, the cluster contains NKp44, a triggering receptor whose expression is limited to NK cells. We identified three new related genes and two gene fragments within a cluster of approximately 200 kb. Two of the three new genes lack charged residues in their transmembrane domain tails. Further, one of the genes contains two potential immunotyrosine Inhibitory motifs in its cytoplasmic tail, suggesting that it delivers inhibitory signals. The human and mouse TREM clusters appear to have diverged such that there are unique sequences in each species. Finally, each gene in the TREM cluster was expressed in a different range of cell types.

Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales

OpenAIRE

Makarova, Kira; Wolf, Yuri; Koonin, Eugene

2015-01-01

With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for...

Organization of nif gene cluster in Frankia sp. EuIK1 strain, a symbiont of Elaeagnus umbellata.

Science.gov (United States)

Oh, Chang Jae; Kim, Ho Bang; Kim, Jitae; Kim, Won Jin; Lee, Hyoungseok; An, Chung Sun

2012-01-01

The nucleotide sequence of a 20.5-kb genomic region harboring nif genes was determined and analyzed. The fragment was obtained from Frankia sp. EuIK1 strain, an indigenous symbiont of Elaeagnus umbellata. A total of 20 ORFs including 12 nif genes were identified and subjected to comparative analysis with the genome sequences of 3 Frankia strains representing diverse host plant specificities. The nucleotide and deduced amino acid sequences showed highest levels of identity with orthologous genes from an Elaeagnus-infecting strain. The gene organization patterns around the nif gene clusters were well conserved among all 4 Frankia strains. However, characteristic features appeared in the location of the nifV gene for each Frankia strain, depending on the type of host plant. Sequence analysis was performed to determine the transcription units and suggested that there could be an independent operon starting from the nifW gene in the EuIK strain. Considering the organization patterns and their total extensions on the genome, we propose that the nif gene clusters remained stable despite genetic variations occurring in the Frankia genomes.

Integrating heterogeneous databases in clustered medic care environments using object-oriented technology

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Thakore, Arun K.; Sauer, Frank

1994-05-01

The organization of modern medical care environments into disease-related clusters, such as a cancer center, a diabetes clinic, etc., has the side-effect of introducing multiple heterogeneous databases, often containing similar information, within the same organization. This heterogeneity fosters incompatibility and prevents the effective sharing of data amongst applications at different sites. Although integration of heterogeneous databases is now feasible, in the medical arena this is often an ad hoc process, not founded on proven database technology or formal methods. In this paper we illustrate the use of a high-level object- oriented semantic association method to model information found in different databases into an integrated conceptual global model that integrates the databases. We provide examples from the medical domain to illustrate an integration approach resulting in a consistent global view, without attacking the autonomy of the underlying databases.

Lactobacillus plantarum gene clusters encoding putative cell-surface protein complexes for carbohydrate utilization are conserved in specific gram-positive bacteria

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Muscariello Lidia

2006-05-01

Full Text Available Abstract Background Genomes of gram-positive bacteria encode many putative cell-surface proteins, of which the majority has no known function. From the rapidly increasing number of available genome sequences it has become apparent that many cell-surface proteins are conserved, and frequently encoded in gene clusters or operons, suggesting common functions, and interactions of multiple components. Results A novel gene cluster encoding exclusively cell-surface proteins was identified, which is conserved in a subgroup of gram-positive bacteria. Each gene cluster generally has one copy of four new gene families called cscA, cscB, cscC and cscD. Clusters encoding these cell-surface proteins were found only in complete genomes of Lactobacillus plantarum, Lactobacillus sakei, Enterococcus faecalis, Listeria innocua, Listeria monocytogenes, Lactococcus lactis ssp lactis and Bacillus cereus and in incomplete genomes of L. lactis ssp cremoris, Lactobacillus casei, Enterococcus faecium, Pediococcus pentosaceus, Lactobacillius brevis, Oenococcus oeni, Leuconostoc mesenteroides, and Bacillus thuringiensis. These genes are neither present in the genomes of streptococci, staphylococci and clostridia, nor in the Lactobacillus acidophilus group, suggesting a niche-specific distribution, possibly relating to association with plants. All encoded proteins have a signal peptide for secretion by the Sec-dependent pathway, while some have cell-surface anchors, novel WxL domains, and putative domains for sugar binding and degradation. Transcriptome analysis in L. plantarum shows that the cscA-D genes are co-expressed, supporting their operon organization. Many gene clusters are significantly up-regulated in a glucose-grown, ccpA-mutant derivative of L. plantarum, suggesting catabolite control. This is supported by the presence of predicted CRE-sites upstream or inside the up-regulated cscA-D gene clusters. Conclusion We propose that the CscA, CscB, CscC and Csc

Server consolidation for heterogeneous computer clusters using Colored Petri Nets and CPN Tools

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Issam Al-Azzoni

2015-10-01

Full Text Available In this paper, we present a new approach to server consolidation in heterogeneous computer clusters using Colored Petri Nets (CPNs. Server consolidation aims to reduce energy costs and improve resource utilization by reducing the number of servers necessary to run the existing virtual machines in the cluster. It exploits the emerging technology of live migration which allows migrating virtual machines between servers without stopping their provided services. Server consolidation approaches attempt to find migration plans that aim to minimize the necessary size of the cluster. Our approach finds plans which not only minimize the overall number of used servers, but also minimize the total data migration overhead. The latter objective is not taken into consideration by other approaches and heuristics. We explore the use of CPN Tools in analyzing the state spaces of the CPNs. Since the state space of the CPN model can grow exponentially with the size of the cluster, we examine different techniques to generate and analyze the state space in order to find good plans to server consolidation within acceptable time and computing power.

A large-scale benchmark of gene prioritization methods.

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Guala, Dimitri; Sonnhammer, Erik L L

2017-04-21

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

Cluster tool for in situ processing and comprehensive characteriza tion of thin films at high temperatures.

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Wenisch, Robert; Lungwitz, Frank; Hanf, Daniel; Heller, Rene; Zscharschuch, Jens; Hübner, René; von Borany, Johannes; Abrasonis, Gintautas; Gemming, Sibylle; Escobar-Galindo, Ramon; Krause, Matthias

2018-05-31

A new cluster tool for in situ real-time processing and depth-resolved compositional, structural and optical characterization of thin films at temperatures from -100 to 800 °C is described. The implemented techniques comprise magnetron sputtering, ion irradiation, Rutherford backscattering spectrometry, Raman spectroscopy and spectroscopic ellipsometry. The capability of the cluster tool is demonstrated for a layer stack MgO/ amorphous Si (~60 nm)/ Ag (~30 nm), deposited at room temperature and crystallized with partial layer exchange by heating up to 650°C. Its initial and final composition, stacking order and structure were monitored in situ in real time and a reaction progress was defined as a function of time and temperature.

Genetic diversity of K-antigen gene clusters of Escherichia coli and their molecular typing using a suspension array.

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Yang, Shuang; Xi, Daoyi; Jing, Fuyi; Kong, Deju; Wu, Junli; Feng, Lu; Cao, Boyang; Wang, Lei

2018-04-01

Capsular polysaccharides (CPSs), or K-antigens, are the major surface antigens of Escherichia coli. More than 80 serologically unique K-antigens are classified into 4 groups (Groups 1-4) of capsules. Groups 1 and 4 contain the Wzy-dependent polymerization pathway and the gene clusters are in the order galF to gnd; Groups 2 and 3 contain the ABC-transporter-dependent pathway and the gene clusters consist of 3 regions, regions 1, 2 and 3. Little is known about the variations among the gene clusters. In this study, 9 serotypes of K-antigen gene clusters (K2ab, K11, K20, K24, K38, K84, K92, K96, and K102) were sequenced and correlated with their CPS chemical structures. On the basis of sequence data, a K-antigen-specific suspension array that detects 10 distinct CPSs, including the above 9 CPSs plus K30, was developed. This is the first report to catalog the genetic features of E. coli K-antigen variations and to develop a suspension array for their molecular typing. The method has a number of advantages over traditional bacteriophage and serum agglutination methods and lays the foundation for straightforward identification and detection of additional K-antigens in the future.

Characterization of the Second LysR-Type Regulator in the Biphenyl-Catabolic Gene Cluster of Pseudomonas pseudoalcaligenes KF707

OpenAIRE

Watanabe, Takahito; Fujihara, Hidehiko; Furukawa, Kensuke

2003-01-01

Pseudomonas pseudoalcaligenes KF707 possesses a biphenyl-catabolic (bph) gene cluster consisting of bphR1A1A2-(orf3)-bphA3A4BCX0X1X2X3D. The bphR1 (formerly orf0) gene product, which belongs to the GntR family, is a positive regulator for itself and bphX0X1X2X3D. Further analysis in this study revealed that a second regulator belonging to the LysR family (designated bphR2) is involved in the regulation of the bph genes in KF707. The bphR2 gene was not located near the bph gene cluster, and it...

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

NARCIS (Netherlands)

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

2014-01-01

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

Voluntary Tools Of The Environmental Oriented Product Policy

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Rusko, Miroslav

2015-06-01

Environmentally oriented product policy is in general determined by the relationships between its aims - subjects - objects - tools. It is based on the integrated approach to the product life cycle, which anticipates an enormous amount of information. It has to solve the questions of the international trade as well as the rules of the International Trade Organization. New forms of preventive environmental strategies and especially Green Marketing are being introduced helping to solve environmental problems and environmental motivation of producers. Many producers face great attention of the public regarding their approach to the environment. Despite the fact that the customers buy products fairly prudently and their behaviour is markedly affected by prices, a particular part of the population prefers the products that do not burden the environment. This brings about a situation, in which the producers within their mutual competition and in relation to customers are enforced to behave responsibly.

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

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Yunhong Zha

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

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

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

2015-10-12

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

An original SERPINA3 gene cluster: Elucidation of genomic organization and gene expression in the Bos taurus 21q24 region

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Ouali Ahmed

2008-04-01

Full Text Available Abstract Background The superfamily of serine proteinase inhibitors (serpins is involved in numerous fundamental biological processes as inflammation, blood coagulation and apoptosis. Our interest is focused on the SERPINA3 sub-family. The major human plasma protease inhibitor, α1-antichymotrypsin, encoded by the SERPINA3 gene, is homologous to genes organized in clusters in several mammalian species. However, although there is a similar genic organization with a high degree of sequence conservation, the reactive-centre-loop domains, which are responsible for the protease specificity, show significant divergences. Results We provide additional information by analyzing the situation of SERPINA3 in the bovine genome. A cluster of eight genes and one pseudogene sharing a high degree of identity and the same structural organization was characterized. Bovine SERPINA3 genes were localized by radiation hybrid mapping on 21q24 and only spanned over 235 Kilobases. For all these genes, we propose a new nomenclature from SERPINA3-1 to SERPINA3-8. They share approximately 70% of identity with the human SERPINA3 homologue. In the cluster, we described an original sub-group of six members with an unexpected high degree of conservation for the reactive-centre-loop domain, suggesting a similar peptidase inhibitory pattern. Preliminary expression analyses of these bovSERPINA3s showed different tissue-specific patterns and diverse states of glycosylation and phosphorylation. Finally, in the context of phylogenetic analyses, we improved our knowledge on mammalian SERPINAs evolution. Conclusion Our experimental results update data of the bovine genome sequencing, substantially increase the bovSERPINA3 sub-family and enrich the phylogenetic tree of serpins. We provide new opportunities for future investigations to approach the biological functions of this unusual subset of serine proteinase inhibitors.

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

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Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at

The entire β-globin gene cluster is deleted in a form of τδβ-thalassemia.

NARCIS (Netherlands)

E.R. Fearon; H.H.Jr. Kazazian; P.G. Waber (Pamela); J.I. Lee (Joseph); S.E. Antonarakis; S.H. Orkin (Stuart); E.F. Vanin; P.S. Henthorn; F.G. Grosveld (Frank); A.F. Scott; G.R. Buchanan

1983-01-01

textabstractWe have used restriction endonuclease mapping to study a deletion involving the beta-globin gene cluster in a Mexican-American family with gamma delta beta-thalassemia. Analysis of DNA polymorphisms demonstrated deletion of the beta-globin gene from the affected chromosome. Using a DNA

Aromatic Polyketide GTRI-02 is a Previously Unidentified Product of the act Gene Cluster in Streptomyces coelicolor A3(2).

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Wu, Changsheng; Ichinose, Koji; Choi, Young Hae; van Wezel, Gilles P

2017-07-18

The biosynthesis of aromatic polyketides derived from type II polyketide synthases (PKSs) is complex, and it is not uncommon that highly similar gene clusters give rise to diverse structural architectures. The act biosynthetic gene cluster (BGC) of the model actinomycete Streptomyces coelicolor A3(2) is an archetypal type II PKS. Here we show that the act BGC also specifies the aromatic polyketide GTRI-02 (1) and propose a mechanism for the biogenesis of its 3,4-dihydronaphthalen-1(2H)-one backbone. Polyketide 1 was also produced by Streptomyces sp. MBT76 after activation of the act-like qin gene cluster by overexpression of the pathway-specific activator. Mining of this strain also identified dehydroxy-GTRI-02 (2), which most likely originated from dehydration of 1 during the isolation process. This work shows that even extensively studied model gene clusters such as act of S. coelicolor can still produce new chemistry, offering new perspectives for drug discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of a gene cloning system in a fast-growing and moderately thermophilic Streptomyces species and heterologous expression of Streptomyces antibiotic biosynthetic gene clusters

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2011-01-01

Background Streptomyces species are a major source of antibiotics. They usually grow slowly at their optimal temperature and fermentation of industrial strains in a large scale often takes a long time, consuming more energy and materials than some other bacterial industrial strains (e.g., E. coli and Bacillus). Most thermophilic Streptomyces species grow fast, but no gene cloning systems have been developed in such strains. Results We report here the isolation of 41 fast-growing (about twice the rate of S. coelicolor), moderately thermophilic (growing at both 30°C and 50°C) Streptomyces strains, detection of one linear and three circular plasmids in them, and sequencing of a 6996-bp plasmid, pTSC1, from one of them. pTSC1-derived pCWH1 could replicate in both thermophilic and mesophilic Streptomyces strains. On the other hand, several Streptomyces replicons function in thermophilic Streptomyces species. By examining ten well-sporulating strains, we found two promising cloning hosts, 2C and 4F. A gene cloning system was established by using the two strains. The actinorhodin and anthramycin biosynthetic gene clusters from mesophilic S. coelicolor A3(2) and thermophilic S. refuineus were heterologously expressed in one of the hosts. Conclusions We have developed a gene cloning and expression system in a fast-growing and moderately thermophilic Streptomyces species. Although just a few plasmids and one antibiotic biosynthetic gene cluster from mesophilic Streptomyces were successfully expressed in thermophilic Streptomyces species, we expect that by utilizing thermophilic Streptomyces-specific promoters, more genes and especially antibiotic genes clusters of mesophilic Streptomyces should be heterologously expressed. PMID:22032628

SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.

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Merelli, Ivan; Calabria, Andrea; Cozzi, Paolo; Viti, Federica; Mosca, Ettore; Milanesi, Luciano

2013-01-01

The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects. We propose a new bioinformatics approach to support biological data mining in the analysis and interpretation of SNPs associated to pathologies. This system can be employed to design custom genotyping chips for disease-oriented studies and to re-score GWAS results. The proposed method relies (1) on the data integration of public resources using a gene-centric database design, (2) on the evaluation of a set of static biomolecular annotations, defined as features, and (3) on the SNP scoring function, which computes SNP scores using parameters and weights set by users. We employed a machine learning classifier to set default feature weights and an ontological annotation layer to enable the enrichment of the input gene set. We implemented our method as a web tool called SNPranker 2.0 (http://www.itb.cnr.it/snpranker), improving our first published release of this system. A user-friendly interface allows the input of a list of genes, SNPs or a biological process, and to customize the features set with relative weights. As result, SNPranker 2.0 returns a list of SNPs, localized within input and ontologically enriched genes, combined with their prioritization scores. Different

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

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Manal Helal

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

Endophytic actinobacteria: Diversity, secondary metabolism and mechanisms to unsilence biosynthetic gene clusters.

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Dinesh, Raghavan; Srinivasan, Veeraraghavan; T E, Sheeja; Anandaraj, Muthuswamy; Srambikkal, Hamza

2017-09-01

Endophytic actinobacteria, which reside in the inner tissues of host plants, are gaining serious attention due to their capacity to produce a plethora of secondary metabolites (e.g. antibiotics) possessing a wide variety of biological activity with diverse functions. This review encompasses the recent reports on endophytic actinobacterial species diversity, in planta habitats and mechanisms underlying their mode of entry into plants. Besides, their metabolic potential, novel bioactive compounds they produce and mechanisms to unravel their hidden metabolic repertoire by activation of cryptic or silent biosynthetic gene clusters (BGCs) for eliciting novel secondary metabolite production are discussed. The study also reviews the classical conservative techniques (chemical/biological/physical elicitation, co-culturing) as well as modern microbiology tools (e.g. next generation sequencing) that are being gainfully employed to uncover the vast hidden scaffolds for novel secondary metabolites produced by these endophytes, which would subsequently herald a revolution in drug engineering. The potential role of these endophytes in the agro-environment as promising biological candidates for inhibition of phytopathogens and the way forward to thoroughly exploit this unique microbial community by inducing expression of cryptic BGCs for encoding unseen products with novel therapeutic properties are also discussed.

Sex differences in young children's use of tools in a problem-solving task : The role of object-oriented play.

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Gredlein, Jeffrey M; Bjorklund, David F

2005-06-01

Three-year-old children were observed in two free-play sessions and participated in a toy-retrieval task, in which only one of six tools could be used to retrieve an out-of-reach toy. Boys engaged in more object-oriented play than girls and were more likely to use tools to retrieve the toy during the baseline tool-use task. All children who did not retrieve the toy during the baseline trials did so after being given a hint, and performance on a transfer-of-training tool-use task approached ceiling levels. This suggests that the sex difference in tool use observed during the baseline phase does not reflect a difference in competency, but rather a sex difference in motivation to interact with objects. Amount of time boys, but not girls, spent in object-oriented play during the free-play sessions predicted performance on the tool-use task. The findings are interpreted in terms of evolutionary theory, consistent with the idea that boys' and girls' play styles evolved to prepare them for adult life in traditional environments.

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

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Heike Hadrys

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

Glycosulfatase-Encoding Gene Cluster in Bifidobacterium breve UCC2003.

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

2016-11-15

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

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

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Litman Gary W

2008-06-01

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

Markerless gene knockout and integration to express heterologous biosynthetic gene clusters in Pseudomonas putida

DEFF Research Database (Denmark)

Choi, Kyeong Rok; Cho, Jae Sung; Cho, In Jin

2018-01-01

Pseudomonas putida has gained much interest among metabolic engineers as a workhorse for producing valuable natural products. While a few gene knockout tools for P. putida have been reported, integration of heterologous genes into the chromosome of P. putida, an essential strategy to develop stable...... plasmid curing systems, generating final strains free of antibiotic markers and plasmids. This markerless recombineering system for efficient gene knockout and integration will expedite metabolic engineering of P. putida, a bacterial host strain of increasing academic and industrial interest....

Mutated genes as research tool

International Nuclear Information System (INIS)

1981-01-01

mutations, it was pointed out that analogous genetical structures exist in all living organisms, the more closely related, the more similar. This is reflected in strikingly similar biochemical pathways, leading from the primary gene message to the ultimate compound or trait. Induced mutations are a unique tool for analysing these gene-controlled pathways, thus leading also to a better understanding of natural evolution

Cadherin genes and evolutionary novelties in the octopus.

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Wang, Z Yan; Ragsdale, Clifton W

2017-09-01

All animals with large brains must have molecular mechanisms to regulate neuronal process outgrowth and prevent neurite self-entanglement. In vertebrates, two major gene families implicated in these mechanisms are the clustered protocadherins and the atypical cadherins. However, the molecular mechanisms utilized in complex invertebrate brains, such as those of the cephalopods, remain largely unknown. Recently, we identified protocadherins and atypical cadherins in the octopus. The octopus protocadherin expansion shares features with the mammalian clustered protocadherins, including enrichment in neural tissues, clustered head-to-tail orientations in the genome, and a large first exon encoding all cadherin domains. Other octopus cadherins, including a newly-identified cadherin with 77 extracellular cadherin domains, are elevated in the suckers, a striking cephalopod novelty. Future study of these octopus genes may yield insights into the general functions of protocadherins in neural wiring and cadherin-related proteins in complex morphogenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing the performance of biomedical clustering methods

DEFF Research Database (Denmark)

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-01-01

expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

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Silaghi Gheorghe Cosmin

2009-05-01

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

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

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Surendra Vikram

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

Voluntary Tools Of The Environmental Oriented Product Policy

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Rusko Miroslav

2015-06-01

Full Text Available Environmentally oriented product policy is in general determined by the relationships between its aims – subjects – objects - tools. It is based on the integrated approach to the product life cycle, which anticipates an enormous amount of information. It has to solve the questions of the international trade as well as the rules of the International Trade Organization. New forms of preventive environmental strategies and especially Green Marketing are being introduced helping to solve environmental problems and environmental motivation of producers. Many producers face great attention of the public regarding their approach to the environment. Despite the fact that the customers buy products fairly prudently and their behaviour is markedly affected by prices, a particular part of the population prefers the products that do not burden the environment. This brings about a situation, in which the producers within their mutual competition and in relation to customers are enforced to behave responsibly.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

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Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

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

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Teng Yi

2012-03-01

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

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

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Yael Garbian

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

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

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

2009-12-01

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

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

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Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2018-02-09

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

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

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Brett A McKinney

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

Deletion of a regulatory gene within the cpk gene cluster reveals novel antibacterial activity in Streptomyces coelicolor A3(2)

NARCIS (Netherlands)

Gottelt, Marco; Kol, Stefan; Gomez-Escribano, Juan Pablo; Bibb, Mervyn; Takano, Eriko

Genome sequencing of Streptomyces coelicolor A3(2) revealed an uncharacterized type I polyketide synthase gene cluster (cpk) Here we describe the discovery of a novel antibacterial activity (abCPK) and a yellow-pigmented secondary metabolite (yCPK) after deleting a presumed pathway-specific

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

Science.gov (United States)

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

2011-01-01

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

NFκB-mediated activation of the cellular FUT3, 5 and 6 gene cluster by herpes simplex virus type 1.

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Nordén, Rickard; Samuelsson, Ebba; Nyström, Kristina

2017-11-01

Herpes simplex virus type 1 has the ability to induce expression of a human gene cluster located on chromosome 19 upon infection. This gene cluster contains three fucosyltransferases (encoded by FUT3, FUT5 and FUT6) with the ability to add a fucose to an N-acetylglucosamine residue. Little is known regarding the transcriptional activation of these three genes in human cells. Intriguingly, herpes simplex virus type 1 activates all three genes simultaneously during infection, a situation not observed in uninfected tissue, pointing towards a virus specific mechanism for transcriptional activation. The aim of this study was to define the underlying mechanism for the herpes simplex virus type 1 activation of FUT3, FUT5 and FUT6 transcription. The transcriptional activation of the FUT-gene cluster on chromosome 19 in fibroblasts was specific, not involving adjacent genes. Moreover, inhibition of NFκB signaling through panepoxydone treatment significantly decreased the induction of FUT3, FUT5 and FUT6 transcriptional activation, as did siRNA targeting of p65, in herpes simplex virus type 1 infected fibroblasts. NFκB and p65 signaling appears to play an important role in the regulation of FUT3, FUT5 and FUT6 transcriptional activation by herpes simplex virus type 1 although additional, unidentified, viral factors might account for part of the mechanism as direct interferon mediated stimulation of NFκB was not sufficient to induce the fucosyltransferase encoding gene cluster in uninfected cells. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cluster-collision frequency. II. Estimation of the collision rate

International Nuclear Information System (INIS)

Amadon, A.S.; Marlow, W.H.

1991-01-01

Gas-phase cluster-collision rates, including effects of cluster morphology and long-range intermolecular forces, are calculated. Identical pairs of icosahedral or dodecahedral carbon tetrachloride clusters of 13, 33, and 55 molecules in two different relative orientations were discussed in the preceding paper [Phys. Rev. A 43, 5483 (1991)]: long-range interaction energies were derived based upon (i) exact calculations of the iterated, or many-body, induced-dipole interaction energies for the clusters in two fixed relative orientations; and (ii) bulk, or continuum descriptions (Lifshitz--van der Waals theory), of spheres of corresponding masses and diameters. In this paper, collision rates are calculated according to an exact description of the rates for small spheres interacting via realistic potentials. Utilizing the interaction energies of the preceding paper, several estimates of the collision rates are given by treating the discrete clusters in fixed relative orientations, by computing rotationally averaged potentials for the discrete clusters, and by approximating the clusters as continuum spheres. For the discrete, highly symmetric clusters treated here, the rates using the rotationally averaged potentials closely approximate the fixed-orientation rates and the values of the intercluster potentials for cluster surface separations under 2 A have negligible effect on the overall collision rates. While the 13-molecule cluster-collision rate differs by 50% from the rate calculated as if the cluster were bulk matter, the two larger cluster-collision rates differ by less than 15% from the macroscopic rates, thereby indicating the transition of microscopic to macroscopic behavior

De novo deletion of HOXB gene cluster in a patient with failure to thrive, developmental delay, gastroesophageal reflux and bronchiectasis.

Science.gov (United States)

Pajusalu, Sander; Reimand, Tiia; Uibo, Oivi; Vasar, Maire; Talvik, Inga; Zilina, Olga; Tammur, Pille; Õunap, Katrin

2015-01-01

We report a female patient with a complex phenotype consisting of failure to thrive, developmental delay, congenital bronchiectasis, gastroesophageal reflux and bilateral inguinal hernias. Chromosomal microarray analysis revealed a 230 kilobase deletion in chromosomal region 17q21.32 (arr[hg19] 17q21.32(46 550 362-46 784 039)×1) encompassing only 9 genes - HOXB1 to HOXB9. The deletion was not found in her mother or father. This is the first report of a patient with a HOXB gene cluster deletion involving only HOXB1 to HOXB9 genes. By comparing our case to previously reported five patients with larger chromosomal aberrations involving the HOXB gene cluster, we can suppose that HOXB gene cluster deletions are responsible for growth retardation, developmental delay, and specific facial dysmorphic features. Also, we suppose that bilateral inguinal hernias, tracheo-esophageal abnormalities, and lung malformations represent features with incomplete penetrance. Interestingly, previously published knock-out mice with targeted heterozygous deletion comparable to our patient did not show phenotypic alterations. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

EERA-DTOC Project: Design Tools for Offshore Wind Farm Clusters; Proyecto EERA-DTOC: herramientas para el diseno de clusters de Parques Eolicos Marinos

Energy Technology Data Exchange (ETDEWEB)

Palomares, A. M.

2015-07-01

In the EERA-DTOC Project an integrated and validated software design tool for the optimization of offshore wind farms and wind farm clusters has been developed. The CIEMAT contribution to this project has change the view on mesoscale wind forecasting models, which were not so far considered capable of modeling wind farm scale phenomena. It has been shown the ability of the WRF model to simulate the wakes caused by the wind turbines on the downwind ones (inter-turbine wakes within a wind farm) as well as the wakes between wind farms within a cluster. (Author)

On the blind use of statistical tools in the analysis of globular cluster stars

Science.gov (United States)

D'Antona, Francesca; Caloi, Vittoria; Tailo, Marco

2018-04-01

As with most data analysis methods, the Bayesian method must be handled with care. We show that its application to determine stellar evolution parameters within globular clusters can lead to paradoxical results if used without the necessary precautions. This is a cautionary tale on the use of statistical tools for big data analysis.

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

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Wolf Yuri I

2007-11-01

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