WorldWideScience

Sample records for genomic scale analysis

  1. Analysis of Genome-Scale Data

    NARCIS (Netherlands)

    Kemmeren, P.P.C.W.

    2005-01-01

    The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has

  2. Analysis of Genome-Scale Data

    OpenAIRE

    Kemmeren, P.P.C.W.

    2005-01-01

    The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has given rise to the parallel development of other high-throughput approaches such as determining mRNA expression level changes, gene-deletion phenotypes, chromosomal location of DNA binding proteins, cel...

  3. Analysis of Aspergillus nidulans metabolism at the genome-scale

    DEFF Research Database (Denmark)

    David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald

    2008-01-01

    of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated...... a function. Results: In this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways......, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene...

  4. Savant Genome Browser 2: visualization and analysis for population-scale genomics.

    Science.gov (United States)

    Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

    2012-07-01

    High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

  5. Kernel methods for large-scale genomic data analysis

    Science.gov (United States)

    Xing, Eric P.; Schaid, Daniel J.

    2015-01-01

    Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today’s explosive data growth in genomics. They provide a practical and principled approach to learning how a large number of genetic variants are associated with complex phenotypes, to help reveal the complexity in the relationship between the genetic markers and the outcome of interest. In this review, we highlight the potential key role it will have in modern genomic data processing, especially with regard to integration with classical methods for gene prioritizing, prediction and data fusion. PMID:25053743

  6. In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

    DEFF Research Database (Denmark)

    Geng, Jun; Nielsen, Jens

    2017-01-01

    The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

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

    Directory of Open Access Journals (Sweden)

    Lee Bernett TK

    2005-01-01

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

  8. Chromosome-scale comparative sequence analysis unravels molecular mechanisms of genome evolution between two wheat cultivars

    KAUST Repository

    Thind, Anupriya Kaur

    2018-02-08

    Background: Recent improvements in DNA sequencing and genome scaffolding have paved the way to generate high-quality de novo assemblies of pseudomolecules representing complete chromosomes of wheat and its wild relatives. These assemblies form the basis to compare the evolutionary dynamics of wheat genomes on a megabase-scale. Results: Here, we provide a comparative sequence analysis of the 700-megabase chromosome 2D between two bread wheat genotypes, the old landrace Chinese Spring and the elite Swiss spring wheat line CH Campala Lr22a. There was a high degree of sequence conservation between the two chromosomes. Analysis of large structural variations revealed four large insertions/deletions (InDels) of >100 kb. Based on the molecular signatures at the breakpoints, unequal crossing over and double-strand break repair were identified as the evolutionary mechanisms that caused these InDels. Three of the large InDels affected copy number of NLRs, a gene family involved in plant immunity. Analysis of single nucleotide polymorphism (SNP) density revealed three haploblocks of 8 Mb, 9 Mb and 48 Mb with a 35-fold increased SNP density compared to the rest of the chromosome. Conclusions: This comparative analysis of two high-quality chromosome assemblies enabled a comprehensive assessment of large structural variations. The insight obtained from this analysis will form the basis of future wheat pan-genome studies.

  9. Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

    Science.gov (United States)

    Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

    2013-06-27

    Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available

  10. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    Directory of Open Access Journals (Sweden)

    Balagurunathan Balaji

    2012-02-01

    Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale

  12. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2014-09-01

    Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

  13. PGen: large-scale genomic variations analysis workflow and browser in SoyKB.

    Science.gov (United States)

    Liu, Yang; Khan, Saad M; Wang, Juexin; Rynge, Mats; Zhang, Yuanxun; Zeng, Shuai; Chen, Shiyuan; Maldonado Dos Santos, Joao V; Valliyodan, Babu; Calyam, Prasad P; Merchant, Nirav; Nguyen, Henry T; Xu, Dong; Joshi, Trupti

    2016-10-06

    With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed "PGen", an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way. We have developed both a Linux version in GitHub ( https://github.com/pegasus-isi/PGen-GenomicVariations-Workflow ) and a web-based implementation of the PGen workflow integrated within the Soybean Knowledge Base (SoyKB), ( http://soykb.org/Pegasus/index.php ). Using PGen, we identified 10,218,140 single-nucleotide polymorphisms (SNPs) and 1,398,982 indels from analysis of 106 soybean lines sequenced at 15X coverage. 297,245 non-synonymous SNPs and 3330 copy number variation (CNV) regions were identified from this analysis. SNPs identified using PGen from additional soybean resequencing projects adding to 500+ soybean germplasm lines in total have been integrated. These SNPs are being utilized for trait improvement using genotype to phenotype prediction approaches developed in-house. In order to browse and access NGS data easily, we have also developed an NGS resequencing data browser ( http://soykb.org/NGS_Resequence/NGS_index.php ) within SoyKB to provide easy access to SNP and downstream analysis results for soybean researchers. PGen workflow has been optimized for the most

  14. GIGGLE: a search engine for large-scale integrated genome analysis

    Science.gov (United States)

    Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

    2018-01-01

    GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation. PMID:29309061

  15. GIGGLE: a search engine for large-scale integrated genome analysis.

    Science.gov (United States)

    Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

    2018-02-01

    GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

  16. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    Energy Technology Data Exchange (ETDEWEB)

    Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

    2016-01-28

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  17. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    International Nuclear Information System (INIS)

    Mader, Kevin; Stampanoni, Marco

    2016-01-01

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures

  18. Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

    Science.gov (United States)

    Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

    2016-05-01

    We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  19. Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

    Directory of Open Access Journals (Sweden)

    Brooks J Paul

    2010-03-01

    Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

  20. GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis.

    Science.gov (United States)

    Gonzalez, Michael A; Lebrigio, Rafael F Acosta; Van Booven, Derek; Ulloa, Rick H; Powell, Eric; Speziani, Fiorella; Tekin, Mustafa; Schüle, Rebecca; Züchner, Stephan

    2013-06-01

    Novel genes are now identified at a rapid pace for many Mendelian disorders, and increasingly, for genetically complex phenotypes. However, new challenges have also become evident: (1) effectively managing larger exome and/or genome datasets, especially for smaller labs; (2) direct hands-on analysis and contextual interpretation of variant data in large genomic datasets; and (3) many small and medium-sized clinical and research-based investigative teams around the world are generating data that, if combined and shared, will significantly increase the opportunities for the entire community to identify new genes. To address these challenges, we have developed GEnomes Management Application (GEM.app), a software tool to annotate, manage, visualize, and analyze large genomic datasets (https://genomics.med.miami.edu/). GEM.app currently contains ∼1,600 whole exomes from 50 different phenotypes studied by 40 principal investigators from 15 different countries. The focus of GEM.app is on user-friendly analysis for nonbioinformaticians to make next-generation sequencing data directly accessible. Yet, GEM.app provides powerful and flexible filter options, including single family filtering, across family/phenotype queries, nested filtering, and evaluation of segregation in families. In addition, the system is fast, obtaining results within 4 sec across ∼1,200 exomes. We believe that this system will further enhance identification of genetic causes of human disease. © 2013 Wiley Periodicals, Inc.

  1. Genome-scale neurogenetics: methodology and meaning.

    Science.gov (United States)

    McCarroll, Steven A; Feng, Guoping; Hyman, Steven E

    2014-06-01

    Genetic analysis is currently offering glimpses into molecular mechanisms underlying such neuropsychiatric disorders as schizophrenia, bipolar disorder and autism. After years of frustration, success in identifying disease-associated DNA sequence variation has followed from new genomic technologies, new genome data resources, and global collaborations that could achieve the scale necessary to find the genes underlying highly polygenic disorders. Here we describe early results from genome-scale studies of large numbers of subjects and the emerging significance of these results for neurobiology.

  2. Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

    Directory of Open Access Journals (Sweden)

    María P. Cortés

    2017-12-01

    Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

  3. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

    Energy Technology Data Exchange (ETDEWEB)

    Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  4. Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

    Science.gov (United States)

    Meilijson, Isaac; Kupiec, Martin; Ruppin, Eytan

    2011-01-01

    We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host. PMID:21909250

  5. Expression induction of P450 genes by imidacloprid in Nilaparvata lugens: A genome-scale analysis.

    Science.gov (United States)

    Zhang, Jianhua; Zhang, Yixi; Wang, Yunchao; Yang, Yuanxue; Cang, Xinzhu; Liu, Zewen

    2016-09-01

    The overexpression of P450 monooxygenase genes is a main mechanism for the resistance to imidacloprid, a representative neonicotinoid insecticide, in Nilaparvata lugens (brown planthopper, BPH). However, only two P450 genes (CYP6AY1 and CYP6ER1), among fifty-four P450 genes identified from BPH genome database, have been reported to play important roles in imidacloprid resistance until now. In this study, after the confirmation of important roles of P450s in imidacloprid resistance by the synergism analysis, the expression induction by imidacloprid was determined for all P450 genes. In the susceptible (Sus) strain, eight P450 genes in Clade4, eight in Clade3 and two in Clade2 were up-regulated by imidacloprid, among which three genes (CYP6CS1, CYP6CW1 and CYP6ER1, all in Clade3) were increased to above 4.0-fold and eight genes to above 2.0-fold. In contrast, no P450 genes were induced in Mito clade. Eight genes induced to above 2.0-fold were selected to determine their expression and induced levels in Huzhou population, in which piperonyl butoxide showed the biggest effects on imidacloprid toxicity among eight field populations. The expression levels of seven P450 genes were higher in Huzhou population than that in Sus strain, with the biggest differences for CYP6CS1 (9.8-fold), CYP6ER1 (7.7-fold) and CYP6AY1 (5.1-fold). The induction levels for all tested genes were bigger in Sus strain than that in Huzhou population except CYP425B1. Screening the induction of P450 genes by imidacloprid in the genome-scale will provide an overall view on the possible metabolic factors in the resistance to neonicotinoid insecticides. The further work, such as the functional study of recombinant proteins, will be performed to validate the roles of these P450s in imidacloprid resistance. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Extreme-Scale De Novo Genome Assembly

    Energy Technology Data Exchange (ETDEWEB)

    Georganas, Evangelos [Intel Corporation, Santa Clara, CA (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Rokhsar, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Yelick, Katherine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.

    2017-09-26

    De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMER, a high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. Genome assembly software has many components, each of which stresses different components of a computer system. This chapter explains the computational challenges involved in each step of the HipMer pipeline, the key distributed data structures, and communication costs in detail. We present performance results of assembling the human genome and the large hexaploid wheat genome on large supercomputers up to tens of thousands of cores.

  7. Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

    Directory of Open Access Journals (Sweden)

    Edgar E. Lara-Ramírez

    2014-01-01

    Full Text Available The increasing number of dengue virus (DENV genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4 has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3 as well as the effective number of codons (ENC, ENCp versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA and clustering analysis on relative synonymous codon usage (RSCU within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution.

  8. Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

    Science.gov (United States)

    Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

    2014-01-01

    The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

  9. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  10. Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis.

    Science.gov (United States)

    Koo, Byoung-Mo; Kritikos, George; Farelli, Jeremiah D; Todor, Horia; Tong, Kenneth; Kimsey, Harvey; Wapinski, Ilan; Galardini, Marco; Cabal, Angelo; Peters, Jason M; Hachmann, Anna-Barbara; Rudner, David Z; Allen, Karen N; Typas, Athanasios; Gross, Carol A

    2017-03-22

    A systems-level understanding of Gram-positive bacteria is important from both an environmental and health perspective and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3,968 and 3,970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Research Guidelines in the Era of Large-scale Collaborations: An Analysis of Genome-wide Association Study Consortia

    Science.gov (United States)

    Austin, Melissa A.; Hair, Marilyn S.; Fullerton, Stephanie M.

    2012-01-01

    Scientific research has shifted from studies conducted by single investigators to the creation of large consortia. Genetic epidemiologists, for example, now collaborate extensively for genome-wide association studies (GWAS). The effect has been a stream of confirmed disease-gene associations. However, effects on human subjects oversight, data-sharing, publication and authorship practices, research organization and productivity, and intellectual property remain to be examined. The aim of this analysis was to identify all research consortia that had published the results of a GWAS analysis since 2005, characterize them, determine which have publicly accessible guidelines for research practices, and summarize the policies in these guidelines. A review of the National Human Genome Research Institute’s Catalog of Published Genome-Wide Association Studies identified 55 GWAS consortia as of April 1, 2011. These consortia were comprised of individual investigators, research centers, studies, or other consortia and studied 48 different diseases or traits. Only 14 (25%) were found to have publicly accessible research guidelines on consortia websites. The available guidelines provide information on organization, governance, and research protocols; half address institutional review board approval. Details of publication, authorship, data-sharing, and intellectual property vary considerably. Wider access to consortia guidelines is needed to establish appropriate research standards with broad applicability to emerging forms of large-scale collaboration. PMID:22491085

  12. Genome-scale analysis of aberrant DNA methylation in colorectal cancer

    Science.gov (United States)

    Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.

    2012-01-01

    Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424

  13. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  14. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

    NARCIS (Netherlands)

    Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

    2006-01-01

    A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for

  15. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

    2015-01-01

    scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

  16. A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis.

    Science.gov (United States)

    Yang, Yilong; Davis, Thomas M

    2017-12-01

    The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Access Array system and 454 sequencing platform. About 24 single-copy or low-copy nuclear genes distributed across the genome were amplified and sequenced from 96 genomic DNA samples representing 16 Fragaria species from diploid (2×) to decaploid (10×), including the most extensive sampling of octoploid taxa yet reported. Individual gene trees were constructed by different tree-building methods. Mosaic genomic structures of diploid Fragaria species consisting of sequences at different phylogenetic positions were observed. Our findings support the presence in octoploid species of genetic signatures from at least five diploid ancestors (F. vesca, F. iinumae, F. bucharica, F. viridis, and at least one additional allele contributor of unknown identity), and questions the extent to which distinct subgenomes are preserved over evolutionary time in the allopolyploid Fragaria species. In addition, our data support divergence between the two wild octoploid species, F. virginiana and F. chiloensis. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  17. Genome scale engineering techniques for metabolic engineering.

    Science.gov (United States)

    Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

    2015-11-01

    Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  18. Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

    Science.gov (United States)

    Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk

    2017-03-01

    Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Large scale analysis of small repeats via mining of the human genome

    NARCIS (Netherlands)

    van den Berg, I.; Bosnacki, D.; Hilbers, P.A.J.

    2009-01-01

    Small repetitive sequences, called tandem repeats, are abundant throughout the human genome, both in coding and in non-coding regions. Their role is still mostly unknown, but at least 20 of those repetitive sequences have been related to neurodegenerative disorders. The mutational process that is

  20. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease

    NARCIS (Netherlands)

    Nalls, Mike A.; Pankratz, Nathan; Lill, Christina M.; Do, Chuong B.; Hernandez, Dena G.; Saad, Mohamad; DeStefano, Anita L.; Kara, Eleanna; Bras, Jose; Sharma, Manu; Schulte, Claudia; Keller, Margaux F.; Arepalli, Sampath; Letson, Christopher; Edsall, Connor; Stefansson, Hreinn; Liu, Xinmin; Pliner, Hannah; Lee, Joseph H.; Cheng, Rong; Ikram, M. Arfan; Ioannidis, John P. A.; Hadjigeorgiou, Georgios M.; Bis, Joshua C.; Martinez, Maria; Perlmutter, Joel S.; Goate, Alison; Marder, Karen; Fiske, Brian; Sutherland, Margaret; Xiromerisiou, Georgia; Myers, Richard H.; Clark, Lorraine N.; Stefansson, Kari; Hardy, John A.; Heutink, Peter; Chen, Honglei; Wood, Nicholas W.; Houlden, Henry; Payami, Haydeh; Brice, Alexis; Scott, William K.; Gasser, Thomas; Bertram, Lars; Eriksson, Nicholas; Foroud, Tatiana; Singleton, Andrew B.; Plagnol, Vincent; Sheerin, Una-Marie; Simón-Sánchez, Javier; Lesage, Suzanne; Sveinbjörnsdóttir, Sigurlaug; Barker, Roger; Ben-Shlomo, Yoav; Berendse, Henk W.; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M. A.; Biffi, Alessandro; Bloem, Bas; Bochdanovits, Zoltan; Bonin, Michael; Bras, Jose M.; Brockmann, Kathrin; Brooks, Janet; Burn, David J.; Charlesworth, Gavin; Chinnery, Patrick F.; Chong, Sean; Clarke, Carl E.; Cookson, Mark R.; Cooper, J. Mark; Corvol, Jean Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean-François; Deloukas, Panos; Deuschl, Günther; Dexter, David T.; van Dijk, Karin D.; Dillman, Allissa; Durif, Frank; Dürr, Alexandra; Edkins, Sarah; Evans, Jonathan R.; Foltynie, Thomas; Dong, Jing; Gardner, Michelle; Gibbs, J. Raphael; Gray, Emma; Guerreiro, Rita; Harris, Clare; van Hilten, Jacobus J.; Hofman, Albert; Hollenbeck, Albert; Holton, Janice; Hu, Michele; Huang, Xuemei; Wurster, Isabel; Mätzler, Walter; Hudson, Gavin; Hunt, Sarah E.; Huttenlocher, Johanna; Illig, Thomas; Jónsson, Pálmi V.; Lambert, Jean-Charles; Langford, Cordelia; Lees, Andrew; Lichtner, Peter; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw R.; Morrison, Karen E.; Mudanohwo, Ese; O'Sullivan, Sean S.; Pearson, Justin; Pétursson, Hjörvar; Pollak, Pierre; Post, Bart; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Shaw, Karen; Shoulson, Ira; Sidransky, Ellen; Smith, Colin; Spencer, Chris C. A.; Stefánsson, Hreinn; Bettella, Francesco; Stockton, Joanna D.; Strange, Amy; Talbot, Kevin; Tanner, Carlie M.; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J.; Uitterlinden, André G.; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H.; Winder-Rhodes, Sophie; Stefánsson, Kári; Hardy, John; Factor, S.; Higgins, D.; Evans, S.; Shill, H.; Stacy, M.; Danielson, J.; Marlor, L.; Williamson, K.; Jankovic, J.; Hunter, C.; Simon, D.; Ryan, P.; Scollins, L.; Saunders-Pullman, R.; Boyar, K.; Costan-Toth, C.; Ohmann, E.; Sudarsky, L.; Joubert, C.; Friedman, J.; Chou, K.; Fernandez, H.; Lannon, M.; Galvez-Jimenez, N.; Podichetty, A.; Thompson, K.; Lewitt, P.; Deangelis, M.; O'Brien, C.; Seeberger, L.; Dingmann, C.; Judd, D.; Marder, K.; Fraser, J.; Harris, J.; Bertoni, J.; Peterson, C.; Rezak, M.; Medalle, G.; Chouinard, S.; Panisset, M.; Hall, J.; Poiffaut, H.; Calabrese, V.; Roberge, P.; Wojcieszek, J.; Belden, J.; Jennings, D.; Marek, K.; Mendick, S.; Reich, S.; Dunlop, B.; Jog, M.; Horn, C.; Uitti, R.; Turk, M.; Ajax, T.; Mannetter, J.; Sethi, K.; Carpenter, J.; Dill, B.; Hatch, L.; Ligon, K.; Narayan, S.; Blindauer, K.; Abou-Samra, K.; Petit, J.; Elmer, L.; Aiken, E.; Davis, K.; Schell, C.; Wilson, S.; Velickovic, M.; Koller, W.; Phipps, S.; Feigin, A.; Gordon, M.; Hamann, J.; Licari, E.; Marotta-Kollarus, M.; Shannon, B.; Winnick, R.; Simuni, T.; Videnovic, A.; Kaczmarek, A.; Williams, K.; Wolff, M.; Rao, J.; Cook, M.; Fernandez, M.; Kostyk, S.; Hubble, J.; Campbell, A.; Reider, C.; Seward, A.; Camicioli, R.; Carter, J.; Nutt, J.; Andrews, P.; Morehouse, S.; Stone, C.; Mendis, T.; Grimes, D.; Alcorn-Costa, C.; Gray, P.; Haas, K.; Vendette, J.; Sutton, J.; Hutchinson, B.; Young, J.; Rajput, A.; Klassen, L.; Shirley, T.; Manyam, B.; Simpson, P.; Whetteckey, J.; Wulbrecht, B.; Truong, D.; Pathak, M.; Frei, K.; Luong, N.; Tra, T.; Tran, A.; Vo, J.; Lang, A.; Kleiner- Fisman, G.; Nieves, A.; Johnston, L.; So, J.; Podskalny, G.; Giffin, L.; Atchison, P.; Allen, C.; Martin, W.; Wieler, M.; Suchowersky, O.; Furtado, S.; Klimek, M.; Hermanowicz, N.; Niswonger, S.; Shults, C.; Fontaine, D.; Aminoff, M.; Christine, C.; Diminno, M.; Hevezi, J.; Dalvi, A.; Kang, U.; Richman, J.; Uy, S.; Sahay, A.; Gartner, M.; Schwieterman, D.; Hall, D.; Leehey, M.; Culver, S.; Derian, T.; Demarcaida, T.; Thurlow, S.; Rodnitzky, R.; Dobson, J.; Lyons, K.; Pahwa, R.; Gales, T.; Thomas, S.; Shulman, L.; Weiner, W.; Dustin, K.; Singer, C.; Zelaya, L.; Tuite, P.; Hagen, V.; Rolandelli, S.; Schacherer, R.; Kosowicz, J.; Gordon, P.; Werner, J.; Serrano, C.; Roque, S.; Kurlan, R.; Berry, D.; Gardiner, I.; Hauser, R.; Sanchez-Ramos, J.; Zesiewicz, T.; Delgado, H.; Price, K.; Rodriguez, P.; Wolfrath, S.; Pfeiffer, R.; Davis, L.; Pfeiffer, B.; Dewey, R.; Hayward, B.; Johnson, A.; Meacham, M.; Estes, B.; Walker, F.; Hunt, V.; O'Neill, C.; Racette, B.; Swisher, L.; Dijamco, Cheri; Conley, Emily Drabant; Dorfman, Elizabeth; Tung, Joyce Y.; Hinds, David A.; Mountain, Joanna L.; Wojcicki, Anne; Lew, M.; Klein, C.; Golbe, L.; Growdon, J.; Wooten, G. F.; Watts, R.; Guttman, M.; Goldwurm, S.; Saint-Hilaire, M. H.; Baker, K.; Litvan, I.; Nicholson, G.; Nance, M.; Drasby, E.; Isaacson, S.; Burn, D.; Pramstaller, P.; Al-hinti, J.; Moller, A.; Sherman, S.; Roxburgh, R.; Slevin, J.; Perlmutter, J.; Mark, M. H.; Huggins, N.; Pezzoli, G.; Massood, T.; Itin, I.; Corbett, A.; Chinnery, P.; Ostergaard, K.; Snow, B.; Cambi, F.; Kay, D.; Samii, A.; Agarwal, P.; Roberts, J. W.; Higgins, D. S.; Molho, Eric; Rosen, Ami; Montimurro, J.; Martinez, E.; Griffith, A.; Kusel, V.; Yearout, D.; Zabetian, C.; Clark, L. N.; Liu, X.; Lee, J. H.; Taub, R. Cheng; Louis, E. D.; Cote, L. J.; Waters, C.; Ford, B.; Fahn, S.; Vance, Jeffery M.; Beecham, Gary W.; Martin, Eden R.; Nuytemans, Karen; Pericak-Vance, Margaret A.; Haines, Jonathan L.; DeStefano, Anita; Seshadri, Sudha; Choi, Seung Hoan; Frank, Samuel; Psaty, Bruce M.; Rice, Kenneth; Longstreth, W. T.; Ton, Thanh G. N.; Jain, Samay; van Duijn, Cornelia M.; Verlinden, Vincent J.; Koudstaal, Peter J.; Singleton, Andrew; Cookson, Mark; Hernandez, Dena; Nalls, Michael; Zonderman, Alan; Ferrucci, Luigi; Johnson, Robert; Longo, Dan; O'Brien, Richard; Traynor, Bryan; Troncoso, Juan; van der Brug, Marcel; Zielke, Ronald; Weale, Michael; Ramasamy, Adaikalavan; Dardiotis, Efthimios; Tsimourtou, Vana; Spanaki, Cleanthe; Plaitakis, Andreas; Bozi, Maria; Stefanis, Leonidas; Vassilatis, Dimitris; Koutsis, Georgios; Panas, Marios; Lunnon, Katie; Lupton, Michelle; Powell, John; Parkkinen, Laura; Ansorge, Olaf

    2014-01-01

    We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were

  1. Large-scale functional genomic analysis of sporulation and meiosis in Saccharomyces cerevisiae.

    OpenAIRE

    Enyenihi, Akon H; Saunders, William S

    2003-01-01

    We have used a single-gene deletion mutant bank to identify the genes required for meiosis and sporulation among 4323 nonessential Saccharomyces cerevisiae annotated open reading frames (ORFs). Three hundred thirty-four sporulation-essential genes were identified, including 78 novel ORFs and 115 known genes without previously described sporulation defects in the comprehensive Saccharomyces Genome (SGD) or Yeast Proteome (YPD) phenotype databases. We have further divided the uncharacterized sp...

  2. Analysing human genomes at different scales

    DEFF Research Database (Denmark)

    Liu, Siyang

    The thriving of the Next-Generation sequencing (NGS) technologies in the past decade has dramatically revolutionized the field of human genetics. We are experiencing a wave of several large-scale whole genome sequencing studies of humans in the world. Those studies vary greatly regarding cohort...... will be reflected by the analysis of real data. This thesis covers studies in two human genome sequencing projects that distinctly differ in terms of studied population, sample size and sequencing depth. In the first project, we sequenced 150 Danish individuals from 50 trio families to 78x coverage....... The sophisticated experimental design enables high-quality de novo assembly of the genomes and provides a good opportunity for mapping the structural variations in the human population. We developed the AsmVar approach to discover, genotype and characterize the structural variations from the assemblies. Our...

  3. Large-scale analysis of antisense transcription in wheat using the Affymetrix GeneChip Wheat Genome Array

    Directory of Open Access Journals (Sweden)

    Settles Matthew L

    2009-05-01

    Full Text Available Abstract Background Natural antisense transcripts (NATs are transcripts of the opposite DNA strand to the sense-strand either at the same locus (cis-encoded or a different locus (trans-encoded. They can affect gene expression at multiple stages including transcription, RNA processing and transport, and translation. NATs give rise to sense-antisense transcript pairs and the number of these identified has escalated greatly with the availability of DNA sequencing resources and public databases. Traditionally, NATs were identified by the alignment of full-length cDNAs or expressed sequence tags to genome sequences, but an alternative method for large-scale detection of sense-antisense transcript pairs involves the use of microarrays. In this study we developed a novel protocol to assay sense- and antisense-strand transcription on the 55 K Affymetrix GeneChip Wheat Genome Array, which is a 3' in vitro transcription (3'IVT expression array. We selected five different tissue types for assay to enable maximum discovery, and used the 'Chinese Spring' wheat genotype because most of the wheat GeneChip probe sequences were based on its genomic sequence. This study is the first report of using a 3'IVT expression array to discover the expression of natural sense-antisense transcript pairs, and may be considered as proof-of-concept. Results By using alternative target preparation schemes, both the sense- and antisense-strand derived transcripts were labeled and hybridized to the Wheat GeneChip. Quality assurance verified that successful hybridization did occur in the antisense-strand assay. A stringent threshold for positive hybridization was applied, which resulted in the identification of 110 sense-antisense transcript pairs, as well as 80 potentially antisense-specific transcripts. Strand-specific RT-PCR validated the microarray observations, and showed that antisense transcription is likely to be tissue specific. For the annotated sense

  4. Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Tyler W. H. Backman

    2018-01-01

    Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

  5. Phylogenetic distribution of large-scale genome patchiness

    Directory of Open Access Journals (Sweden)

    Hackenberg Michael

    2008-04-01

    Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

  6. Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Liu, Lifang; Feizi, Amir; Osterlund, Tobias

    2014-01-01

    related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three a-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER......Background: The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due...... to the poorly annotated proteome. Results: Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely...

  7. Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

    Science.gov (United States)

    Liu, Lifang; Feizi, Amir; Österlund, Tobias; Hjort, Carsten; Nielsen, Jens

    2014-06-24

    The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.

  8. A genome-scale integration and analysis of Lactococcus lactis translation data.

    Directory of Open Access Journals (Sweden)

    Julien Racle

    Full Text Available Protein synthesis is a template polymerization process composed by three main steps: initiation, elongation, and termination. During translation, ribosomes are engaged into polysomes whose size is used for the quantitative characterization of translatome. However, simultaneous transcription and translation in the bacterial cytosol complicates the analysis of translatome data. We established a procedure for robust estimation of the ribosomal density in hundreds of genes from Lactococcus lactis polysome size measurements. We used a mechanistic model of translation to integrate the information about the ribosomal density and for the first time we estimated the protein synthesis rate for each gene and identified the rate limiting steps. Contrary to conventional considerations, we find significant number of genes to be elongation limited. This number increases during stress conditions compared to optimal growth and proteins synthesized at maximum rate are predominantly elongation limited. Consistent with bacterial physiology, we found proteins with similar rate and control characteristics belonging to the same functional categories. Under stress conditions, we found that synthesis rate of regulatory proteins is becoming comparable to proteins favored under optimal growth. These findings suggest that the coupling of metabolic states and protein synthesis is more important than previously thought.

  9. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

  10. Robust and rapid algorithms facilitate large-scale whole genome sequencing downstream analysis in an integrative framework.

    Science.gov (United States)

    Li, Miaoxin; Li, Jiang; Li, Mulin Jun; Pan, Zhicheng; Hsu, Jacob Shujui; Liu, Dajiang J; Zhan, Xiaowei; Wang, Junwen; Song, Youqiang; Sham, Pak Chung

    2017-05-19

    Whole genome sequencing (WGS) is a promising strategy to unravel variants or genes responsible for human diseases and traits. However, there is a lack of robust platforms for a comprehensive downstream analysis. In the present study, we first proposed three novel algorithms, sequence gap-filled gene feature annotation, bit-block encoded genotypes and sectional fast access to text lines to address three fundamental problems. The three algorithms then formed the infrastructure of a robust parallel computing framework, KGGSeq, for integrating downstream analysis functions for whole genome sequencing data. KGGSeq has been equipped with a comprehensive set of analysis functions for quality control, filtration, annotation, pathogenic prediction and statistical tests. In the tests with whole genome sequencing data from 1000 Genomes Project, KGGSeq annotated several thousand more reliable non-synonymous variants than other widely used tools (e.g. ANNOVAR and SNPEff). It took only around half an hour on a small server with 10 CPUs to access genotypes of ∼60 million variants of 2504 subjects, while a popular alternative tool required around one day. KGGSeq's bit-block genotype format used 1.5% or less space to flexibly represent phased or unphased genotypes with multiple alleles and achieved a speed of over 1000 times faster to calculate genotypic correlation. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment

    KAUST Repository

    Rapakoulia, Trisevgeni

    2017-08-09

    Motivation: Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential of increasing the therapeutic effect, while reducing the likelihood of drug resistance. In order to reduce time and cost spent in comprehensive screens, methods are needed which can model additive effects of possible drug combinations. Results: We here show that the transcriptional response to combinatorial drug treatment at promoters, as measured by single molecule CAGE technology, is accurately described by a linear combination of the responses of the individual drugs at a genome wide scale. We also find that the same linear relationship holds for transcription at enhancer elements. We conclude that the described approach is promising for eliciting the transcriptional response to multidrug treatment at promoters and enhancers in an unbiased genome wide way, which may minimize the need for exhaustive combinatorial screens.

  12. Genome‐scale diversity and niche adaptation analysis of Lactococcus lactis by comparative genome hybridization using multi‐strain arrays

    Science.gov (United States)

    Siezen, Roland J.; Bayjanov, Jumamurat R.; Felis, Giovanna E.; van der Sijde, Marijke R.; Starrenburg, Marjo; Molenaar, Douwe; Wels, Michiel; van Hijum, Sacha A. F. T.; van Hylckama Vlieg, Johan E. T.

    2011-01-01

    Summary Lactococcus lactis produces lactic acid and is widely used in the manufacturing of various fermented dairy products. However, the species is also frequently isolated from non‐dairy niches, such as fermented plant material. Recently, these non‐dairy strains have gained increasing interest, as they have been described to possess flavour‐forming activities that are rarely found in dairy isolates and have diverse metabolic properties. We performed an extensive whole‐genome diversity analysis on 39 L. lactis strains, isolated from dairy and plant sources. Comparative genome hybridization analysis with multi‐strain microarrays was used to assess presence or absence of genes and gene clusters in these strains, relative to all L. lactis sequences in public databases, whereby chromosomal and plasmid‐encoded genes were computationally analysed separately. Nearly 3900 chromosomal orthologous groups (chrOGs) were defined on basis of four sequenced chromosomes of L. lactis strains (IL1403, KF147, SK11, MG1363). Of these, 1268 chrOGs are present in at least 35 strains and represent the presently known core genome of L. lactis, and 72 chrOGs appear to be unique for L. lactis. Nearly 600 and 400 chrOGs were found to be specific for either the subspecies lactis or subspecies cremoris respectively. Strain variability was found in presence or absence of gene clusters related to growth on plant substrates, such as genes involved in the consumption of arabinose, xylan, α‐galactosides and galacturonate. Further niche‐specific differences were found in gene clusters for exopolysaccharides biosynthesis, stress response (iron transport, osmotolerance) and bacterial defence mechanisms (nisin biosynthesis). Strain variability of functions encoded on known plasmids included proteolysis, lactose fermentation, citrate uptake, metal ion resistance and exopolysaccharides biosynthesis. The present study supports the view of L. lactis as a species with a very flexible

  13. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

  14. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4.

    LENUS (Irish Health Repository)

    Sklar, Pamela

    2011-10-01

    We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10(-7)). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci.

  15. The OME Framework for genome-scale systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)

    2014-12-19

    The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale

  16. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

    Science.gov (United States)

    Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

    2016-01-01

    The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

  17. A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis

    OpenAIRE

    Yang, Yilong; Davis, Thomas M

    2017-01-01

    Abstract The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Ac...

  18. Constraining genome-scale models to represent the bow tie structure of metabolism for 13C metabolic flux analysis

    DEFF Research Database (Denmark)

    Backman, Tyler W.H.; Ando, David; Singh, Jahnavi

    2018-01-01

    for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S- 13C MFA, as well as provide for a substantially lower set of flux bounds......Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used...

  19. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

  20. Ensembl Genomes 2013: scaling up access to genome-wide data.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Hughes, Daniel Seth Toney; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Langridge, Nicholas; McDowall, Mark D; Maheswari, Uma; Maslen, Gareth; Nuhn, Michael; Ong, Chuang Kee; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Tuli, Mary Ann; Walts, Brandon; Williams, Gareth; Wilson, Derek; Youens-Clark, Ken; Monaco, Marcela K; Stein, Joshua; Wei, Xuehong; Ware, Doreen; Bolser, Daniel M; Howe, Kevin Lee; Kulesha, Eugene; Lawson, Daniel; Staines, Daniel Michael

    2014-01-01

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.

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

    Directory of Open Access Journals (Sweden)

    Cohn Zachary A

    2007-06-01

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

  2. Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach.

    Science.gov (United States)

    Knies, David; Wittmüß, Philipp; Appel, Sebastian; Sawodny, Oliver; Ederer, Michael; Feuer, Ronny

    2015-10-28

    The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA) that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

  3. Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach

    Directory of Open Access Journals (Sweden)

    David Knies

    2015-10-01

    Full Text Available The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

  4. The Genome-Scale Integrated Networks in Microorganisms

    Directory of Open Access Journals (Sweden)

    Tong Hao

    2018-02-01

    Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

  5. Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

    Science.gov (United States)

    Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

    2012-01-01

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

  6. Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies.

    Science.gov (United States)

    Demirkan, A; Lahti, J; Direk, N; Viktorin, A; Lunetta, K L; Terracciano, A; Nalls, M A; Tanaka, T; Hek, K; Fornage, M; Wellmann, J; Cornelis, M C; Ollila, H M; Yu, L; Smith, J A; Pilling, L C; Isaacs, A; Palotie, A; Zhuang, W V; Zonderman, A; Faul, J D; Sutin, A; Meirelles, O; Mulas, A; Hofman, A; Uitterlinden, A; Rivadeneira, F; Perola, M; Zhao, W; Salomaa, V; Yaffe, K; Luik, A I; Liu, Y; Ding, J; Lichtenstein, P; Landén, M; Widen, E; Weir, D R; Llewellyn, D J; Murray, A; Kardia, S L R; Eriksson, J G; Koenen, K; Magnusson, P K E; Ferrucci, L; Mosley, T H; Cucca, F; Oostra, B A; Bennett, D A; Paunio, T; Berger, K; Harris, T B; Pedersen, N L; Murabito, J M; Tiemeier, H; van Duijn, C M; Räikkönen, K

    2016-06-01

    Major depressive disorder (MDD) is moderately heritable, however genome-wide association studies (GWAS) for MDD, as well as for related continuous outcomes, have not shown consistent results. Attempts to elucidate the genetic basis of MDD may be hindered by heterogeneity in diagnosis. The Center for Epidemiological Studies Depression (CES-D) scale provides a widely used tool for measuring depressive symptoms clustered in four different domains which can be combined together into a total score but also can be analysed as separate symptom domains. We performed a meta-analysis of GWAS of the CES-D symptom clusters. We recruited 12 cohorts with the 20- or 10-item CES-D scale (32 528 persons). One single nucleotide polymorphism (SNP), rs713224, located near the brain-expressed melatonin receptor (MTNR1A) gene, was associated with the somatic complaints domain of depression symptoms, with borderline genome-wide significance (p discovery = 3.82 × 10-8). The SNP was analysed in an additional five cohorts comprising the replication sample (6813 persons). However, the association was not consistent among the replication sample (p discovery+replication = 1.10 × 10-6) with evidence of heterogeneity. Despite the effort to harmonize the phenotypes across cohorts and participants, our study is still underpowered to detect consistent association for depression, even by means of symptom classification. On the contrary, the SNP-based heritability and co-heritability estimation results suggest that a very minor part of the variation could be captured by GWAS, explaining the reason of sparse findings.

  7. Big Data Analysis of Human Genome Variations

    KAUST Repository

    Gojobori, Takashi

    2016-01-25

    Since the human genome draft sequence was in public for the first time in 2000, genomic analyses have been intensively extended to the population level. The following three international projects are good examples for large-scale studies of human genome variations: 1) HapMap Data (1,417 individuals) (http://hapmap.ncbi.nlm.nih.gov/downloads/genotypes/2010-08_phaseII+III/forward/), 2) HGDP (Human Genome Diversity Project) Data (940 individuals) (http://www.hagsc.org/hgdp/files.html), 3) 1000 genomes Data (2,504 individuals) http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/ If we can integrate all three data into a single volume of data, we should be able to conduct a more detailed analysis of human genome variations for a total number of 4,861 individuals (= 1,417+940+2,504 individuals). In fact, we successfully integrated these three data sets by use of information on the reference human genome sequence, and we conducted the big data analysis. In particular, we constructed a phylogenetic tree of about 5,000 human individuals at the genome level. As a result, we were able to identify clusters of ethnic groups, with detectable admixture, that were not possible by an analysis of each of the three data sets. Here, we report the outcome of this kind of big data analyses and discuss evolutionary significance of human genomic variations. Note that the present study was conducted in collaboration with Katsuhiko Mineta and Kosuke Goto at KAUST.

  8. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  9. Genome based analysis of a novel Chloroflexi in full-scale anaerobic digesters treating waste activated sludge

    DEFF Research Database (Denmark)

    McIlroy, Simon Jon; Kirkegaard, Rasmus Hansen; Albertsen, Mads

    Key to optimised design and operation of full-scale anaerobic digesters is an understanding of the organisms responsible. As one of the most abundant phyla in these systems, the Chloroflexi likely make a substantial contribute to system function. Here we apply state-of-the-art molecular methods t...

  10. Genomic divergences among cattle, dog and human estimated from large-scale alignments of genomic sequences

    Directory of Open Access Journals (Sweden)

    Shade Larry L

    2006-06-01

    Full Text Available Abstract Background Approximately 11 Mb of finished high quality genomic sequences were sampled from cattle, dog and human to estimate genomic divergences and their regional variation among these lineages. Results Optimal three-way multi-species global sequence alignments for 84 cattle clones or loci (each >50 kb of genomic sequence were constructed using the human and dog genome assemblies as references. Genomic divergences and substitution rates were examined for each clone and for various sequence classes under different functional constraints. Analysis of these alignments revealed that the overall genomic divergences are relatively constant (0.32–0.37 change/site for pairwise comparisons among cattle, dog and human; however substitution rates vary across genomic regions and among different sequence classes. A neutral mutation rate (2.0–2.2 × 10(-9 change/site/year was derived from ancestral repetitive sequences, whereas the substitution rate in coding sequences (1.1 × 10(-9 change/site/year was approximately half of the overall rate (1.9–2.0 × 10(-9 change/site/year. Relative rate tests also indicated that cattle have a significantly faster rate of substitution as compared to dog and that this difference is about 6%. Conclusion This analysis provides a large-scale and unbiased assessment of genomic divergences and regional variation of substitution rates among cattle, dog and human. It is expected that these data will serve as a baseline for future mammalian molecular evolution studies.

  11. Meta-Analysis of Heterogeneous Data Sources for Genome-Scale Identification of Risk Genes in Complex Phenotypes

    DEFF Research Database (Denmark)

    Pers, Tune Hannes; Hansen, Niclas Tue; Hansen, Kasper Lage

    2011-01-01

    Meta‐analyses of large‐scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome‐wide association (GWA) studies, protein......) with an odds ratio of 1.28 [1.12–1.48], which replicates a previous case‐control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available...

  12. Comparative Genome Analysis and Genome Evolution

    NARCIS (Netherlands)

    Snel, Berend

    2002-01-01

    This thesis described a collection of bioinformatic analyses on complete genome sequence data. We have studied the evolution of gene content and find that vertical inheritance dominates over horizontal gene trasnfer, even to the extent that we can use the gene content to make genome phylogenies.

  13. Predicting the accumulation of storage compounds by Rhodococcus jostii RHA1 in the feast-famine growth cycles using genome-scale flux balance analysis.

    Science.gov (United States)

    Tajparast, Mohammad; Frigon, Dominic

    2018-01-01

    Feast-famine cycles in biological wastewater resource recovery systems select for bacterial species that accumulate intracellular storage compounds such as poly-β-hydroxybutyrate (PHB), glycogen, and triacylglycerols (TAG). These species survive better the famine phase and resume rapid substrate uptake at the beginning of the feast phase faster than microorganisms unable to accumulate storage. However, ecophysiological conditions favouring the accumulation of either storage compounds remain to be clarified, and predictive capabilities need to be developed to eventually rationally design reactors producing these compounds. Using a genome-scale metabolic modelling approach, the storage metabolism of Rhodococcus jostii RHA1 was investigated for steady-state feast-famine cycles on glucose and acetate as the sole carbon sources. R. jostii RHA1 is capable of accumulating the three storage compounds (PHB, TAG, and glycogen) simultaneously. According to the experimental observations, when glucose was the substrate, feast phase chemical oxygen demand (COD) accumulation was similar for the three storage compounds; when acetate was the substrate, however, PHB accumulation was 3 times higher than TAG accumulation and essentially no glycogen was accumulated. These results were simulated using the genome-scale metabolic model of R. jostii RHA1 (iMT1174) by means of flux balance analysis (FBA) to determine the objective functions capable of predicting these behaviours. Maximization of the growth rate was set as the main objective function, while minimization of total reaction fluxes and minimization of metabolic adjustment (environmental MOMA) were considered as the sub-objective functions. The environmental MOMA sub-objective performed better than the minimization of total reaction fluxes sub-objective function at predicting the mixture of storage compounds accumulated. Additional experiments with 13C-labelled bicarbonate (HCO3-) found that the fluxes through the central

  14. Multidimensional scaling for large genomic data sets

    Directory of Open Access Journals (Sweden)

    Lu Henry

    2008-04-01

    Full Text Available Abstract Background Multi-dimensional scaling (MDS is aimed to represent high dimensional data in a low dimensional space with preservation of the similarities between data points. This reduction in dimensionality is crucial for analyzing and revealing the genuine structure hidden in the data. For noisy data, dimension reduction can effectively reduce the effect of noise on the embedded structure. For large data set, dimension reduction can effectively reduce information retrieval complexity. Thus, MDS techniques are used in many applications of data mining and gene network research. However, although there have been a number of studies that applied MDS techniques to genomics research, the number of analyzed data points was restricted by the high computational complexity of MDS. In general, a non-metric MDS method is faster than a metric MDS, but it does not preserve the true relationships. The computational complexity of most metric MDS methods is over O(N2, so that it is difficult to process a data set of a large number of genes N, such as in the case of whole genome microarray data. Results We developed a new rapid metric MDS method with a low computational complexity, making metric MDS applicable for large data sets. Computer simulation showed that the new method of split-and-combine MDS (SC-MDS is fast, accurate and efficient. Our empirical studies using microarray data on the yeast cell cycle showed that the performance of K-means in the reduced dimensional space is similar to or slightly better than that of K-means in the original space, but about three times faster to obtain the clustering results. Our clustering results using SC-MDS are more stable than those in the original space. Hence, the proposed SC-MDS is useful for analyzing whole genome data. Conclusion Our new method reduces the computational complexity from O(N3 to O(N when the dimension of the feature space is far less than the number of genes N, and it successfully

  15. Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

    Directory of Open Access Journals (Sweden)

    Kim Tae

    2011-06-01

    Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

  16. Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

    Science.gov (United States)

    Klier, Christine

    2012-03-06

    The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

  17. Large-scale analysis of full-length cDNAs from the tomato (Solanum lycopersicum) cultivar Micro-Tom, a reference system for the Solanaceae genomics.

    Science.gov (United States)

    Aoki, Koh; Yano, Kentaro; Suzuki, Ayako; Kawamura, Shingo; Sakurai, Nozomu; Suda, Kunihiro; Kurabayashi, Atsushi; Suzuki, Tatsuya; Tsugane, Taneaki; Watanabe, Manabu; Ooga, Kazuhide; Torii, Maiko; Narita, Takanori; Shin-I, Tadasu; Kohara, Yuji; Yamamoto, Naoki; Takahashi, Hideki; Watanabe, Yuichiro; Egusa, Mayumi; Kodama, Motoichiro; Ichinose, Yuki; Kikuchi, Mari; Fukushima, Sumire; Okabe, Akiko; Arie, Tsutomu; Sato, Yuko; Yazawa, Katsumi; Satoh, Shinobu; Omura, Toshikazu; Ezura, Hiroshi; Shibata, Daisuke

    2010-03-30

    The Solanaceae family includes several economically important vegetable crops. The tomato (Solanum lycopersicum) is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance. To accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs) was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706) was estimated to be 0.061%. The collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the tomato whole-genome sequence and aid in tomato functional

  18. Large-scale analysis of full-length cDNAs from the tomato (Solanum lycopersicum cultivar Micro-Tom, a reference system for the Solanaceae genomics

    Directory of Open Access Journals (Sweden)

    Kikuchi Mari

    2010-03-01

    Full Text Available Abstract Background The Solanaceae family includes several economically important vegetable crops. The tomato (Solanum lycopersicum is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance. Results To accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706 was estimated to be 0.061%. Conclusion The collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the

  19. Big Data Analysis of Human Genome Variations

    KAUST Repository

    Gojobori, Takashi

    2016-01-01

    Since the human genome draft sequence was in public for the first time in 2000, genomic analyses have been intensively extended to the population level. The following three international projects are good examples for large-scale studies of human

  20. The integrated microbial genome resource of analysis.

    Science.gov (United States)

    Checcucci, Alice; Mengoni, Alessio

    2015-01-01

    Integrated Microbial Genomes and Metagenomes (IMG) is a biocomputational system that allows to provide information and support for annotation and comparative analysis of microbial genomes and metagenomes. IMG has been developed by the US Department of Energy (DOE)-Joint Genome Institute (JGI). IMG platform contains both draft and complete genomes, sequenced by Joint Genome Institute and other public and available genomes. Genomes of strains belonging to Archaea, Bacteria, and Eukarya domains are present as well as those of viruses and plasmids. Here, we provide some essential features of IMG system and case study for pangenome analysis.

  1. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  2. Insertion Sequence-Caused Large Scale-Rearrangements in the Genome of Escherichia coli

    Science.gov (United States)

    2016-07-18

    affordable ap- proach to genome-wide characterization of genetic varia - tion in bacterial and eukaryotic genomes (1–3). In addition to small-scale...Paired-End Reads), that uses a graph-based al- gorithm (27) capable of detecting most large-scale varia - tion involving repetitive regions, including novel...Avila,P., Grinsted,J. and De La Cruz,F. (1988) Analysis of the variable endpoints generated by one-ended transposition of Tn21.. J. Bacteriol., 170

  3. Exploring Networks at the genome scale

    NARCIS (Netherlands)

    Lam, M.C.; Puchalka, J.; Diez, M.S.; Martins Dos Santos, V.A.P.

    2010-01-01

    Systems biology is aimed at achieving a holistic understanding of living organisms, while synthetic biology seeks to design and construct new living organisms with targeted functionalities. Genome sequencing and the fields of ‘omics’ technology have proven a goldmine of information for scientists

  4. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  5. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

    DEFF Research Database (Denmark)

    Zeggini, Eleftheria; Scott, Laura J; Saxena, Richa

    2008-01-01

    analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample......Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published...

  6. Reconstruction and in silico analysis of an Actinoplanes sp. SE50/110 genome-scale metabolic model for acarbose production

    Directory of Open Access Journals (Sweden)

    Yali eWang

    2015-06-01

    Full Text Available Actinoplanes sp. SE50/110 produces the -glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites and 1219 reactions. 122 and 81 genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78% and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110.

  7. FGWAS: Functional genome wide association analysis.

    Science.gov (United States)

    Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

    2017-10-01

    Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Decoding Synteny Blocks and Large-Scale Duplications in Mammalian and Plant Genomes

    Science.gov (United States)

    Peng, Qian; Alekseyev, Max A.; Tesler, Glenn; Pevzner, Pavel A.

    The existing synteny block reconstruction algorithms use anchors (e.g., orthologous genes) shared over all genomes to construct the synteny blocks for multiple genomes. This approach, while efficient for a few genomes, cannot be scaled to address the need to construct synteny blocks in many mammalian genomes that are currently being sequenced. The problem is that the number of anchors shared among all genomes quickly decreases with the increase in the number of genomes. Another problem is that many genomes (plant genomes in particular) had extensive duplications, which makes decoding of genomic architecture and rearrangement analysis in plants difficult. The existing synteny block generation algorithms in plants do not address the issue of generating non-overlapping synteny blocks suitable for analyzing rearrangements and evolution history of duplications. We present a new algorithm based on the A-Bruijn graph framework that overcomes these difficulties and provides a unified approach to synteny block reconstruction for multiple genomes, and for genomes with large duplications.

  9. Large-scale genomic 2D visualization reveals extensive CG-AT skew correlation in bird genomes

    Directory of Open Access Journals (Sweden)

    Deng Xuemei

    2007-11-01

    Full Text Available Abstract Background Bird genomes have very different compositional structure compared with other warm-blooded animals. The variation in the base skew rules in the vertebrate genomes remains puzzling, but it must relate somehow to large-scale genome evolution. Current research is inclined to relate base skew with mutations and their fixation. Here we wish to explore base skew correlations in bird genomes, to develop methods for displaying and quantifying such correlations at different scales, and to discuss possible explanations for the peculiarities of the bird genomes in skew correlation. Results We have developed a method called Base Skew Double Triangle (BSDT for exhibiting the genome-scale change of AT/CG skew as a two-dimensional square picture, showing base skews at many scales simultaneously in a single image. By this method we found that most chicken chromosomes have high AT/CG skew correlation (symmetry in 2D picture, except for some microchromosomes. No other organisms studied (18 species show such high skew correlations. This visualized high correlation was validated by three kinds of quantitative calculations with overlapping and non-overlapping windows, all indicating that chicken and birds in general have a special genome structure. Similar features were also found in some of the mammal genomes, but clearly much weaker than in chickens. We presume that the skew correlation feature evolved near the time that birds separated from other vertebrate lineages. When we eliminated the repeat sequences from the genomes, the AT and CG skews correlation increased for some mammal genomes, but were still clearly lower than in chickens. Conclusion Our results suggest that BSDT is an expressive visualization method for AT and CG skew and enabled the discovery of the very high skew correlation in bird genomes; this peculiarity is worth further study. Computational analysis indicated that this correlation might be a compositional characteristic

  10. Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system.

    Science.gov (United States)

    Speth, Daan R; In 't Zandt, Michiel H; Guerrero-Cruz, Simon; Dutilh, Bas E; Jetten, Mike S M

    2016-03-31

    Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date.

  11. Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

    Science.gov (United States)

    Chechetkin, V R; Lobzin, V V

    2017-08-07

    Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  13. GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing.

    Science.gov (United States)

    Wang, Xuewen; Wang, Le

    2016-01-01

    Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

  14. Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

    OpenAIRE

    Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

    2016-01-01

    Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete d...

  15. Large-scale parallel genome assembler over cloud computing environment.

    Science.gov (United States)

    Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

    2017-06-01

    The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

  16. Large Scale Genome Analysis Shows that the Epitopes for Broadly Cross-Reactive Antibodies Are Predominant in the Pandemic 2009 Influenza Virus A H1N1 Strain

    Directory of Open Access Journals (Sweden)

    Edgar E. Lara-Ramírez

    2013-11-01

    Full Text Available The past pandemic strain H1N1 (A (H1N1pdm09 has now become a common component of current seasonal influenza viruses. It has changed the pre-existing immunity of the human population to succeeding infections. In the present study, a total of 14,210 distinct sequences downloaded from National Center for Biotechnology Information (NCBI database were used for the analysis. The epitope compositions in A (H1N1pdm09, classic seasonal strains, swine strains as well as highly virulent avian strain H5N1, identified with the aid of the Immune Epitope DataBase (IEDB, were compared at genomic level. The result showed that A (H1N1 pdm09 contains the 90% of B-cell epitopes for broadly cross-reactive antibodies (EBCA, which is in consonance with the recent reports on the experimental identification of new epitopes or antibodies for this virus and the binding tests with influenza virus protein HA of different subtypes. Our analysis supports that high proportional EBCA depends on the epitope pattern of A (H1N1pdm09 virus. This study may be helpful for better understanding of A (H1N1pdm09 and the production of new influenza vaccines.

  17. Multi-scale structural community organisation of the human genome.

    Science.gov (United States)

    Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

    2017-04-11

    Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

  18. Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

    Science.gov (United States)

    Mackey, Aaron J; Pearson, William R

    2004-10-01

    Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

  19. H2@Scale Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, Mark

    2017-07-12

    'H2@Scale' is a concept based on the opportunity for hydrogen to act as an intermediate between energy sources and uses. Hydrogen has the potential to be used like the primary intermediate in use today, electricity, because it too is fungible. This presentation summarizes the H2@Scale analysis efforts performed during the first third of 2017. Results of technical potential uses and supply options are summarized and show that the technical potential demand for hydrogen is 60 million metric tons per year and that the U.S. has sufficient domestic resources to meet that demand. A high level infrastructure analysis is also presented that shows an 85% increase in energy on the grid if all hydrogen is produced from grid electricity. However, a preliminary spatial assessment shows that supply is sufficient in most counties across the U.S. The presentation also shows plans for analysis of the economic potential for the H2@Scale concept. Those plans involve developing supply and demand curves for potential hydrogen generation options and as compared to other options for use of that hydrogen.

  20. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  1. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  2. Analysis of metabolic networks of Streptomyces leeuwenhoekii C34 by means of a genome scale model: Prediction of modifications that enhance the production of specialized metabolites.

    Science.gov (United States)

    Razmilic, Valeria; Castro, Jean F; Andrews, Barbara; Asenjo, Juan A

    2018-07-01

    The first genome scale model (GSM) for Streptomyces leeuwenhoekii C34 was developed to study the biosynthesis pathways of specialized metabolites and to find metabolic engineering targets for enhancing their production. The model, iVR1007, consists of 1,722 reactions, 1,463 metabolites, and 1,007 genes, it includes the biosynthesis pathways of chaxamycins, chaxalactins, desferrioxamines, ectoine, and other specialized metabolites. iVR1007 was validated using experimental information of growth on 166 different sources of carbon, nitrogen and phosphorous, showing an 83.7% accuracy. The model was used to predict metabolic engineering targets for enhancing the biosynthesis of chaxamycins and chaxalactins. Gene knockouts, such as sle03600 (L-homoserine O-acetyltransferase), and sle39090 (trehalose-phosphate synthase), that enhance the production of the specialized metabolites by increasing the pool of precursors were identified. Using the algorithm of flux scanning based on enforced objective flux (FSEOF) implemented in python, 35 and 25 over-expression targets for increasing the production of chaxamycin A and chaxalactin A, respectively, that were not directly associated with their biosynthesis routes were identified. Nineteen over-expression targets that were common to the two specialized metabolites studied, like the over-expression of the acetyl carboxylase complex (sle47660 (accA) and any of the following genes: sle44630 (accA_1) or sle39830 (accA_2) or sle27560 (bccA) or sle59710) were identified. The predicted knockouts and over-expression targets will be used to perform metabolic engineering of S. leeuwenhoekii C34 and obtain overproducer strains. © 2018 Wiley Periodicals, Inc.

  3. GWAMA: software for genome-wide association meta-analysis

    Directory of Open Access Journals (Sweden)

    Mägi Reedik

    2010-05-01

    Full Text Available Abstract Background Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. Results We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. Conclusions The GWAMA (Genome-Wide Association Meta-Analysis software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.

  4. Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

    Science.gov (United States)

    Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

    2016-09-01

    Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.

  5. Metabolite coupling in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard Ø

    2006-03-01

    Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

  6. Genome-scale metabolic representation of Amycolatopsis balhimycina

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Figueiredo, L. F.; Förster, Jochen

    2012-01-01

    Infection caused by methicillin‐resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin...... to reconstruct a genome‐scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC‐genome (∼69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR...

  7. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

  8. Short and long-term genome stability analysis of prokaryotic genomes.

    Science.gov (United States)

    Brilli, Matteo; Liò, Pietro; Lacroix, Vincent; Sagot, Marie-France

    2013-05-08

    Gene organization dynamics is actively studied because it provides useful evolutionary information, makes functional annotation easier and often enables to characterize pathogens. There is therefore a strong interest in understanding the variability of this trait and the possible correlations with life-style. Two kinds of events affect genome organization: on one hand translocations and recombinations change the relative position of genes shared by two genomes (i.e. the backbone gene order); on the other, insertions and deletions leave the backbone gene order unchanged but they alter the gene neighborhoods by breaking the syntenic regions. A complete picture about genome organization evolution therefore requires to account for both kinds of events. We developed an approach where we model chromosomes as graphs on which we compute different stability estimators; we consider genome rearrangements as well as the effect of gene insertions and deletions. In a first part of the paper, we fit a measure of backbone gene order conservation (hereinafter called backbone stability) against phylogenetic distance for over 3000 genome comparisons, improving existing models for the divergence in time of backbone stability. Intra- and inter-specific comparisons were treated separately to focus on different time-scales. The use of multiple genomes of a same species allowed to identify genomes with diverging gene order with respect to their conspecific. The inter-species analysis indicates that pathogens are more often unstable with respect to non-pathogens. In a second part of the text, we show that in pathogens, gene content dynamics (insertions and deletions) have a much more dramatic effect on genome organization stability than backbone rearrangements. In this work, we studied genome organization divergence taking into account the contribution of both genome order rearrangements and genome content dynamics. By studying species with multiple sequenced genomes available, we were

  9. Power Laws, Scale-Free Networks and Genome Biology

    CERN Document Server

    Koonin, Eugene V; Karev, Georgy P

    2006-01-01

    Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for disco...

  10. Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

    OpenAIRE

    Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

    2017-01-01

    Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

  11. GRIMP: A web- and grid-based tool for high-speed analysis of large-scale genome-wide association using imputed data.

    NARCIS (Netherlands)

    K. Estrada Gil (Karol); A. Abuseiris (Anis); F.G. Grosveld (Frank); A.G. Uitterlinden (André); T.A. Knoch (Tobias); F. Rivadeneira Ramirez (Fernando)

    2009-01-01

    textabstractThe current fast growth of genome-wide association studies (GWAS) combined with now common computationally expensive imputation requires the online access of large user groups to high-performance computing resources capable of analyzing rapidly and efficiently millions of genetic

  12. Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

    Science.gov (United States)

    Song, Yun S.

    2012-01-01

    Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and

  13. Genome Sequencing and Analysis Conference IV

    Energy Technology Data Exchange (ETDEWEB)

    1993-12-31

    J. Craig Venter and C. Thomas Caskey co-chaired Genome Sequencing and Analysis Conference IV held at Hilton Head, South Carolina from September 26--30, 1992. Venter opened the conference by noting that approximately 400 researchers from 16 nations were present four times as many participants as at Genome Sequencing Conference I in 1989. Venter also introduced the Data Fair, a new component of the conference allowing exchange and on-site computer analysis of unpublished sequence data.

  14. Encyclopedia of bacterial gene circuits whose presence or absence correlate with pathogenicity--a large-scale system analysis of decoded bacterial genomes.

    Science.gov (United States)

    Shestov, Maksim; Ontañón, Santiago; Tozeren, Aydin

    2015-10-13

    Bacterial infections comprise a global health challenge as the incidences of antibiotic resistance increase. Pathogenic potential of bacteria has been shown to be context dependent, varying in response to environment and even within the strains of the same genus. We used the KEGG repository and extensive literature searches to identify among the 2527 bacterial genomes in the literature those implicated as pathogenic to the host, including those which show pathogenicity in a context dependent manner. Using data on the gene contents of these genomes, we identified sets of genes highly abundant in pathogenic but relatively absent in commensal strains and vice versa. In addition, we carried out genome comparison within a genus for the seventeen largest genera in our genome collection. We projected the resultant lists of ortholog genes onto KEGG bacterial pathways to identify clusters and circuits, which can be linked to either pathogenicity or synergy. Gene circuits relatively abundant in nonpathogenic bacteria often mediated biosynthesis of antibiotics. Other synergy-linked circuits reduced drug-induced toxicity. Pathogen-abundant gene circuits included modules in one-carbon folate, two-component system, type-3 secretion system, and peptidoglycan biosynthesis. Antibiotics-resistant bacterial strains possessed genes modulating phagocytosis, vesicle trafficking, cytoskeletal reorganization, and regulation of the inflammatory response. Our study also identified bacterial genera containing a circuit, elements of which were previously linked to Alzheimer's disease. Present study produces for the first time, a signature, in the form of a robust list of gene circuitry whose presence or absence could potentially define the pathogenicity of a microbiome. Extensive literature search substantiated a bulk majority of the commensal and pathogenic circuitry in our predicted list. Scanning microbiome libraries for these circuitry motifs will provide further insights into the complex

  15. Exploratory analysis of genomic segmentations with Segtools

    Directory of Open Access Journals (Sweden)

    Buske Orion J

    2011-10-01

    Full Text Available Abstract Background As genome-wide experiments and annotations become more prevalent, researchers increasingly require tools to help interpret data at this scale. Many functional genomics experiments involve partitioning the genome into labeled segments, such that segments sharing the same label exhibit one or more biochemical or functional traits. For example, a collection of ChlP-seq experiments yields a compendium of peaks, each labeled with one or more associated DNA-binding proteins. Similarly, manually or automatically generated annotations of functional genomic elements, including cis-regulatory modules and protein-coding or RNA genes, can also be summarized as genomic segmentations. Results We present a software toolkit called Segtools that simplifies and automates the exploration of genomic segmentations. The software operates as a series of interacting tools, each of which provides one mode of summarization. These various tools can be pipelined and summarized in a single HTML page. We describe the Segtools toolkit and demonstrate its use in interpreting a collection of human histone modification data sets and Plasmodium falciparum local chromatin structure data sets. Conclusions Segtools provides a convenient, powerful means of interpreting a genomic segmentation.

  16. Comparative Genome Analysis of Enterobacter cloacae

    Science.gov (United States)

    Liu, Wing-Yee; Wong, Chi-Fat; Chung, Karl Ming-Kar; Jiang, Jing-Wei; Leung, Frederick Chi-Ching

    2013-01-01

    The Enterobacter cloacae species includes an extremely diverse group of bacteria that are associated with plants, soil and humans. Publication of the complete genome sequence of the plant growth-promoting endophytic E. cloacae subsp. cloacae ENHKU01 provided an opportunity to perform the first comparative genome analysis between strains of this dynamic species. Examination of the pan-genome of E. cloacae showed that the conserved core genome retains the general physiological and survival genes of the species, while genomic factors in plasmids and variable regions determine the virulence of the human pathogenic E. cloacae strain; additionally, the diversity of fimbriae contributes to variation in colonization and host determination of different E. cloacae strains. Comparative genome analysis further illustrated that E. cloacae strains possess multiple mechanisms for antagonistic action against other microorganisms, which involve the production of siderophores and various antimicrobial compounds, such as bacteriocins, chitinases and antibiotic resistance proteins. The presence of Type VI secretion systems is expected to provide further fitness advantages for E. cloacae in microbial competition, thus allowing it to survive in different environments. Competition assays were performed to support our observations in genomic analysis, where E. cloacae subsp. cloacae ENHKU01 demonstrated antagonistic activities against a wide range of plant pathogenic fungal and bacterial species. PMID:24069314

  17. Microbial genome analysis: the COG approach.

    Science.gov (United States)

    Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

    2017-09-14

    For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

  18. Mathematical Analysis of Genomic Evolution

    Directory of Open Access Journals (Sweden)

    Cedric Green

    2011-01-01

    Full Text Available Changes in nucleotide sequences, or mutations, accumulate from generation to generation in the genomes of all living organisms. The mutations can be advantageous, deleterious, or neutral. The goal of this project is to determine the amount of advantageous mutations it takes to get human (Homo sapiens DNA from the DNA of genetically distinct organisms. We do this by collecting the genomic data of such organisms, and estimating the amount of mutations it takes to transform yeast (Saccharomyces cerevisiae DNA to the DNA of a human. We calculate the typical number of mutations occurring annually through the organism's average life span and the average mutation rate. This allows us to determine the total number of mutations as well as the probability of advantageous mutations. Not surprisingly, this probability proves to be fairly small. A more precise estimate can be determined by accounting for the differences in the chromosomal structure and phenomena like horizontal gene transfer.

  19. Large-Scale Sequencing: The Future of Genomic Sciences Colloquium

    Energy Technology Data Exchange (ETDEWEB)

    Margaret Riley; Merry Buckley

    2009-01-01

    Genetic sequencing and the various molecular techniques it has enabled have revolutionized the field of microbiology. Examining and comparing the genetic sequences borne by microbes - including bacteria, archaea, viruses, and microbial eukaryotes - provides researchers insights into the processes microbes carry out, their pathogenic traits, and new ways to use microorganisms in medicine and manufacturing. Until recently, sequencing entire microbial genomes has been laborious and expensive, and the decision to sequence the genome of an organism was made on a case-by-case basis by individual researchers and funding agencies. Now, thanks to new technologies, the cost and effort of sequencing is within reach for even the smallest facilities, and the ability to sequence the genomes of a significant fraction of microbial life may be possible. The availability of numerous microbial genomes will enable unprecedented insights into microbial evolution, function, and physiology. However, the current ad hoc approach to gathering sequence data has resulted in an unbalanced and highly biased sampling of microbial diversity. A well-coordinated, large-scale effort to target the breadth and depth of microbial diversity would result in the greatest impact. The American Academy of Microbiology convened a colloquium to discuss the scientific benefits of engaging in a large-scale, taxonomically-based sequencing project. A group of individuals with expertise in microbiology, genomics, informatics, ecology, and evolution deliberated on the issues inherent in such an effort and generated a set of specific recommendations for how best to proceed. The vast majority of microbes are presently uncultured and, thus, pose significant challenges to such a taxonomically-based approach to sampling genome diversity. However, we have yet to even scratch the surface of the genomic diversity among cultured microbes. A coordinated sequencing effort of cultured organisms is an appropriate place to begin

  20. Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

    Science.gov (United States)

    Cao, Yinhe; Tung, Wen-Wen; Gao, J B

    2004-01-01

    With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

  1. Toward the automated generation of genome-scale metabolic networks in the SEED.

    Science.gov (United States)

    DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

    2007-04-26

    Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

  2. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  3. A Distance Measure for Genome Phylogenetic Analysis

    Science.gov (United States)

    Cao, Minh Duc; Allison, Lloyd; Dix, Trevor

    Phylogenetic analyses of species based on single genes or parts of the genomes are often inconsistent because of factors such as variable rates of evolution and horizontal gene transfer. The availability of more and more sequenced genomes allows phylogeny construction from complete genomes that is less sensitive to such inconsistency. For such long sequences, construction methods like maximum parsimony and maximum likelihood are often not possible due to their intensive computational requirement. Another class of tree construction methods, namely distance-based methods, require a measure of distances between any two genomes. Some measures such as evolutionary edit distance of gene order and gene content are computational expensive or do not perform well when the gene content of the organisms are similar. This study presents an information theoretic measure of genetic distances between genomes based on the biological compression algorithm expert model. We demonstrate that our distance measure can be applied to reconstruct the consensus phylogenetic tree of a number of Plasmodium parasites from their genomes, the statistical bias of which would mislead conventional analysis methods. Our approach is also used to successfully construct a plausible evolutionary tree for the γ-Proteobacteria group whose genomes are known to contain many horizontally transferred genes.

  4. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  5. BFAST: an alignment tool for large scale genome resequencing.

    Directory of Open Access Journals (Sweden)

    Nils Homer

    2009-11-01

    Full Text Available The new generation of massively parallel DNA sequencers, combined with the challenge of whole human genome resequencing, result in the need for rapid and accurate alignment of billions of short DNA sequence reads to a large reference genome. Speed is obviously of great importance, but equally important is maintaining alignment accuracy of short reads, in the 25-100 base range, in the presence of errors and true biological variation.We introduce a new algorithm specifically optimized for this task, as well as a freely available implementation, BFAST, which can align data produced by any of current sequencing platforms, allows for user-customizable levels of speed and accuracy, supports paired end data, and provides for efficient parallel and multi-threaded computation on a computer cluster. The new method is based on creating flexible, efficient whole genome indexes to rapidly map reads to candidate alignment locations, with arbitrary multiple independent indexes allowed to achieve robustness against read errors and sequence variants. The final local alignment uses a Smith-Waterman method, with gaps to support the detection of small indels.We compare BFAST to a selection of large-scale alignment tools -- BLAT, MAQ, SHRiMP, and SOAP -- in terms of both speed and accuracy, using simulated and real-world datasets. We show BFAST can achieve substantially greater sensitivity of alignment in the context of errors and true variants, especially insertions and deletions, and minimize false mappings, while maintaining adequate speed compared to other current methods. We show BFAST can align the amount of data needed to fully resequence a human genome, one billion reads, with high sensitivity and accuracy, on a modest computer cluster in less than 24 hours. BFAST is available at (http://bfast.sourceforge.net.

  6. Genomic analysis of Fusarium verticillioides.

    Science.gov (United States)

    Brown, D W; Butchko, R A E; Proctor, R H

    2008-09-01

    Fusarium verticillioides (teleomorph Gibberella moniliformis) can be either an endophyte of maize, causing no visible disease, or a pathogen-causing disease of ears, stalks, roots and seedlings. At any stage, this fungus can synthesize fumonisins, a family of mycotoxins structurally similar to the sphingolipid sphinganine. Ingestion of fumonisin-contaminated maize has been associated with a number of animal diseases, including cancer in rodents, and exposure has been correlated with human oesophageal cancer in some regions of the world, and some evidence suggests that fumonisins are a risk factor for neural tube defects. A primary goal of the authors' laboratory is to eliminate fumonisin contamination of maize and maize products. Understanding how and why these toxins are made and the F. verticillioides-maize disease process will allow one to develop novel strategies to limit tissue destruction (rot) and fumonisin production. To meet this goal, genomic sequence data, expressed sequence tags (ESTs) and microarrays are being used to identify F. verticillioides genes involved in the biosynthesis of toxins and plant pathogenesis. This paper describes the current status of F. verticillioides genomic resources and three approaches being used to mine microarray data from a wild-type strain cultured in liquid fumonisin production medium for 12, 24, 48, 72, 96 and 120h. Taken together, these approaches demonstrate the power of microarray technology to provide information on different biological processes.

  7. Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

    Science.gov (United States)

    Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

    2015-01-01

    The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

  8. Environmental versatility promotes modularity in genome-scale metabolic networks.

    Science.gov (United States)

    Samal, Areejit; Wagner, Andreas; Martin, Olivier C

    2011-08-24

    The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple

  9. Environmental versatility promotes modularity in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2011-08-01

    Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional

  10. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  11. Whole genome sequence analysis of Mycobacterium suricattae

    KAUST Repository

    Dippenaar, Anzaan; Parsons, Sven David Charles; Sampson, Samantha Leigh; Van Der Merwe, Ruben Gerhard; Drewe, Julian Ashley; Abdallah, Abdallah; Siame, Kabengele Keith; Gey Van Pittius, Nicolaas Claudius; Van Helden, Paul David; Pain, Arnab; Warren, Robin Mark

    2015-01-01

    Tuberculosis occurs in various mammalian hosts and is caused by a range of different lineages of the Mycobacterium tuberculosis complex (MTBC). A recently described member, Mycobacterium suricattae, causes tuberculosis in meerkats (Suricata suricatta) in Southern Africa and preliminary genetic analysis showed this organism to be closely related to an MTBC pathogen of rock hyraxes (Procavia capensis), the dassie bacillus. Here we make use of whole genome sequencing to describe the evolution of the genome of M. suricattae, including known and novel regions of difference, SNPs and IS6110 insertion sites. We used genome-wide phylogenetic analysis to show that M. suricattae clusters with the chimpanzee bacillus, previously isolated from a chimpanzee (Pan troglodytes) in West Africa. We propose an evolutionary scenario for the Mycobacterium africanum lineage 6 complex, showing the evolutionary relationship of M. africanum and chimpanzee bacillus, and the closely related members M. suricattae, dassie bacillus and Mycobacterium mungi.

  12. Whole genome sequence analysis of Mycobacterium suricattae

    KAUST Repository

    Dippenaar, Anzaan

    2015-10-21

    Tuberculosis occurs in various mammalian hosts and is caused by a range of different lineages of the Mycobacterium tuberculosis complex (MTBC). A recently described member, Mycobacterium suricattae, causes tuberculosis in meerkats (Suricata suricatta) in Southern Africa and preliminary genetic analysis showed this organism to be closely related to an MTBC pathogen of rock hyraxes (Procavia capensis), the dassie bacillus. Here we make use of whole genome sequencing to describe the evolution of the genome of M. suricattae, including known and novel regions of difference, SNPs and IS6110 insertion sites. We used genome-wide phylogenetic analysis to show that M. suricattae clusters with the chimpanzee bacillus, previously isolated from a chimpanzee (Pan troglodytes) in West Africa. We propose an evolutionary scenario for the Mycobacterium africanum lineage 6 complex, showing the evolutionary relationship of M. africanum and chimpanzee bacillus, and the closely related members M. suricattae, dassie bacillus and Mycobacterium mungi.

  13. Primer to analysis of genomic data using R

    CERN Document Server

    Gondro, Cedric

    2015-01-01

    Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics or for use in lab sessions. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher’s website.  Chapters show how to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R. A wide range of R packages useful for working with genomic data are illustrated with practical examples. In recent years R has b...

  14. Estimating phylogenetic trees from genome-scale data.

    Science.gov (United States)

    Liu, Liang; Xi, Zhenxiang; Wu, Shaoyuan; Davis, Charles C; Edwards, Scott V

    2015-12-01

    The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data. © 2015 New York Academy of Sciences.

  15. Multi-scale coding of genomic information: From DNA sequence to genome structure and function

    International Nuclear Information System (INIS)

    Arneodo, Alain; Vaillant, Cedric; Audit, Benjamin; Argoul, Francoise; D'Aubenton-Carafa, Yves; Thermes, Claude

    2011-01-01

    Understanding how chromatin is spatially and dynamically organized in the nucleus of eukaryotic cells and how this affects genome functions is one of the main challenges of cell biology. Since the different orders of packaging in the hierarchical organization of DNA condition the accessibility of DNA sequence elements to trans-acting factors that control the transcription and replication processes, there is actually a wealth of structural and dynamical information to learn in the primary DNA sequence. In this review, we show that when using concepts, methodologies, numerical and experimental techniques coming from statistical mechanics and nonlinear physics combined with wavelet-based multi-scale signal processing, we are able to decipher the multi-scale sequence encoding of chromatin condensation-decondensation mechanisms that play a fundamental role in regulating many molecular processes involved in nuclear functions.

  16. A protocol for generating a high-quality genome-scale metabolic reconstruction.

    Science.gov (United States)

    Thiele, Ines; Palsson, Bernhard Ø

    2010-01-01

    Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

  17. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  18. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  19. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

  20. Comparative genome analysis of Basidiomycete fungi

    Energy Technology Data Exchange (ETDEWEB)

    Riley, Robert; Salamov, Asaf; Henrissat, Bernard; Nagy, Laszlo; Brown, Daren; Held, Benjamin; Baker, Scott; Blanchette, Robert; Boussau, Bastien; Doty, Sharon L.; Fagnan, Kirsten; Floudas, Dimitris; Levasseur, Anthony; Manning, Gerard; Martin, Francis; Morin, Emmanuelle; Otillar, Robert; Pisabarro, Antonio; Walton, Jonathan; Wolfe, Ken; Hibbett, David; Grigoriev, Igor

    2013-08-07

    Fungi of the phylum Basidiomycota (basidiomycetes), make up some 37percent of the described fungi, and are important in forestry, agriculture, medicine, and bioenergy. This diverse phylum includes symbionts, pathogens, and saprotrophs including the majority of wood decaying and ectomycorrhizal species. To better understand the genetic diversity of this phylum we compared the genomes of 35 basidiomycetes including 6 newly sequenced genomes. These genomes span extremes of genome size, gene number, and repeat content. Analysis of core genes reveals that some 48percent of basidiomycete proteins are unique to the phylum with nearly half of those (22percent) found in only one organism. Correlations between lifestyle and certain gene families are evident. Phylogenetic patterns of plant biomass-degrading genes in Agaricomycotina suggest a continuum rather than a dichotomy between the white rot and brown rot modes of wood decay. Based on phylogenetically-informed PCA analysis of wood decay genes, we predict that that Botryobasidium botryosum and Jaapia argillacea have properties similar to white rot species, although neither has typical ligninolytic class II fungal peroxidases (PODs). This prediction is supported by growth assays in which both fungi exhibit wood decay with white rot-like characteristics. Based on this, we suggest that the white/brown rot dichotomy may be inadequate to describe the full range of wood decaying fungi. Analysis of the rate of discovery of proteins with no or few homologs suggests the value of continued sequencing of basidiomycete fungi.

  1. Spiritual Competency Scale: Further Analysis

    Science.gov (United States)

    Dailey, Stephanie F.; Robertson, Linda A.; Gill, Carman S.

    2015-01-01

    This article describes a follow-up analysis of the Spiritual Competency Scale, which initially validated ASERVIC's (Association for Spiritual, Ethical and Religious Values in Counseling) spiritual competencies. The study examined whether the factor structure of the Spiritual Competency Scale would be supported by participants (i.e., ASERVIC…

  2. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  3. Techniques for Large-Scale Bacterial Genome Manipulation and Characterization of the Mutants with Respect to In Silico Metabolic Reconstructions.

    Science.gov (United States)

    diCenzo, George C; Finan, Turlough M

    2018-01-01

    The rate at which all genes within a bacterial genome can be identified far exceeds the ability to characterize these genes. To assist in associating genes with cellular functions, a large-scale bacterial genome deletion approach can be employed to rapidly screen tens to thousands of genes for desired phenotypes. Here, we provide a detailed protocol for the generation of deletions of large segments of bacterial genomes that relies on the activity of a site-specific recombinase. In this procedure, two recombinase recognition target sequences are introduced into known positions of a bacterial genome through single cross-over plasmid integration. Subsequent expression of the site-specific recombinase mediates recombination between the two target sequences, resulting in the excision of the intervening region and its loss from the genome. We further illustrate how this deletion system can be readily adapted to function as a large-scale in vivo cloning procedure, in which the region excised from the genome is captured as a replicative plasmid. We next provide a procedure for the metabolic analysis of bacterial large-scale genome deletion mutants using the Biolog Phenotype MicroArray™ system. Finally, a pipeline is described, and a sample Matlab script is provided, for the integration of the obtained data with a draft metabolic reconstruction for the refinement of the reactions and gene-protein-reaction relationships in a metabolic reconstruction.

  4. Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

    Directory of Open Access Journals (Sweden)

    Bharat Manna

    2017-10-01

    Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

  5. Estimated allele substitution effects underlying genomic evaluation models depend on the scaling of allele counts

    NARCIS (Netherlands)

    Bouwman, Aniek C.; Hayes, Ben J.; Calus, Mario P.L.

    2017-01-01

    Background: Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of

  6. Comparative Genomic Analysis of Soybean Flowering Genes

    Science.gov (United States)

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

    2012-01-01

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

  7. PGSB/MIPS Plant Genome Information Resources and Concepts for the Analysis of Complex Grass Genomes.

    Science.gov (United States)

    Spannagl, Manuel; Bader, Kai; Pfeifer, Matthias; Nussbaumer, Thomas; Mayer, Klaus F X

    2016-01-01

    PGSB (Plant Genome and Systems Biology; formerly MIPS-Munich Institute for Protein Sequences) has been involved in developing, implementing and maintaining plant genome databases for more than a decade. Genome databases and analysis resources have focused on individual genomes and aim to provide flexible and maintainable datasets for model plant genomes as a backbone against which experimental data, e.g., from high-throughput functional genomics, can be organized and analyzed. In addition, genomes from both model and crop plants form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny) between related species on macro- and micro-levels.The genomes of many economically important Triticeae plants such as wheat, barley, and rye present a great challenge for sequence assembly and bioinformatic analysis due to their enormous complexity and large genome size. Novel concepts and strategies have been developed to deal with these difficulties and have been applied to the genomes of wheat, barley, rye, and other cereals. This includes the GenomeZipper concept, reference-guided exome assembly, and "chromosome genomics" based on flow cytometry sorted chromosomes.

  8. Whole genome sequencing and bioinformatics analysis of two Egyptian genomes.

    Science.gov (United States)

    ElHefnawi, Mahmoud; Jeon, Sungwon; Bhak, Youngjune; ElFiky, Asmaa; Horaiz, Ahmed; Jun, JeHoon; Kim, Hyunho; Bhak, Jong

    2018-05-15

    We report two Egyptian male genomes (EGP1 and EGP2) sequenced at ~ 30× sequencing depths. EGP1 had 4.7 million variants, where 198,877 were novel variants while EGP2 had 209,109 novel variants out of 4.8 million variants. The mitochondrial haplogroup of the two individuals were identified to be H7b1 and L2a1c, respectively. We also identified the Y haplogroup of EGP1 (R1b) and EGP2 (J1a2a1a2 > P58 > FGC11). EGP1 had a mutation in the NADH gene of the mitochondrial genome ND4 (m.11778 G > A) that causes Leber's hereditary optic neuropathy. Some SNPs shared by the two genomes were associated with an increased level of cholesterol and triglycerides, probably related with Egyptians obesity. Comparison of these genomes with African and Western-Asian genomes can provide insights on Egyptian ancestry and genetic history. This resource can be used to further understand genomic diversity and functional classification of variants as well as human migration and evolution across Africa and Western-Asia. Copyright © 2017. Published by Elsevier B.V.

  9. Genome-wide comparative analysis of four Indian Drosophila species.

    Science.gov (United States)

    Mohanty, Sujata; Khanna, Radhika

    2017-12-01

    Comparative analysis of multiple genomes of closely or distantly related Drosophila species undoubtedly creates excitement among evolutionary biologists in exploring the genomic changes with an ecology and evolutionary perspective. We present herewith the de novo assembled whole genome sequences of four Drosophila species, D. bipectinata, D. takahashii, D. biarmipes and D. nasuta of Indian origin using Next Generation Sequencing technology on an Illumina platform along with their detailed assembly statistics. The comparative genomics analysis, e.g. gene predictions and annotations, functional and orthogroup analysis of coding sequences and genome wide SNP distribution were performed. The whole genome of Zaprionus indianus of Indian origin published earlier by us and the genome sequences of previously sequenced 12 Drosophila species available in the NCBI database were included in the analysis. The present work is a part of our ongoing genomics project of Indian Drosophila species.

  10. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Science.gov (United States)

    Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

    2017-01-01

    Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

  11. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Directory of Open Access Journals (Sweden)

    Marko Budinich

    Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

  12. Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

    Science.gov (United States)

    Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

    2015-01-20

    While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

  13. Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

    Science.gov (United States)

    Nowrousian, Minou; Würtz, Christian; Pöggeler, Stefanie; Kück, Ulrich

    2004-03-01

    One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

  14. Mapping copy number variation by population-scale genome sequencing

    DEFF Research Database (Denmark)

    Mills, Ryan E.; Walter, Klaudia; Stewart, Chip

    2011-01-01

    Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is......, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications...

  15. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  16. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.

    2003-01-01

    The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

  17. CoCoNUT: an efficient system for the comparison and analysis of genomes

    Directory of Open Access Journals (Sweden)

    Kurtz Stefan

    2008-11-01

    Full Text Available Abstract Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit that allows solving several different tasks in a unified framework: (1 finding regions of high similarity among multiple genomic sequences and aligning them, (2 comparing two draft or multi-chromosomal genomes, (3 locating large segmental duplications in large genomic sequences, and (4 mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component, CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics.

  18. Data for constructing insect genome content matrices for phylogenetic analysis and functional annotation

    Directory of Open Access Journals (Sweden)

    Jeffrey Rosenfeld

    2016-03-01

    Full Text Available Twenty one fully sequenced and well annotated insect genomes were used to construct genome content matrices for phylogenetic analysis and functional annotation of insect genomes. To examine the role of e-value cutoff in ortholog determination we used scaled e-value cutoffs and a single linkage clustering approach.. The present communication includes (1 a list of the genomes used to construct the genome content phylogenetic matrices, (2 a nexus file with the data matrices used in phylogenetic analysis, (3 a nexus file with the Newick trees generated by phylogenetic analysis, (4 an excel file listing the Core (CORE genes and Unique (UNI genes found in five insect groups, and (5 a figure showing a plot of consistency index (CI versus percent of unannotated genes that are apomorphies in the data set for gene losses and gains and bar plots of gains and losses for four consistency index (CI cutoffs.

  19. Genome wide characterization of simple sequence repeats in watermelon genome and their application in comparative mapping and genetic diversity analysis.

    Science.gov (United States)

    Zhu, Huayu; Song, Pengyao; Koo, Dal-Hoe; Guo, Luqin; Li, Yanman; Sun, Shouru; Weng, Yiqun; Yang, Luming

    2016-08-05

    Microsatellite markers are one of the most informative and versatile DNA-based markers used in plant genetic research, but their development has traditionally been difficult and costly. The whole genome sequencing with next-generation sequencing (NGS) technologies provides large amounts of sequence data to develop numerous microsatellite markers at whole genome scale. SSR markers have great advantage in cross-species comparisons and allow investigation of karyotype and genome evolution through highly efficient computation approaches such as in silico PCR. Here we described genome wide development and characterization of SSR markers in the watermelon (Citrullus lanatus) genome, which were then use in comparative analysis with two other important crop species in the Cucurbitaceae family: cucumber (Cucumis sativus L.) and melon (Cucumis melo L.). We further applied these markers in evaluating the genetic diversity and population structure in watermelon germplasm collections. A total of 39,523 microsatellite loci were identified from the watermelon draft genome with an overall density of 111 SSRs/Mbp, and 32,869 SSR primers were designed with suitable flanking sequences. The dinucleotide SSRs were the most common type representing 34.09 % of the total SSR loci and the AT-rich motifs were the most abundant in all nucleotide repeat types. In silico PCR analysis identified 832 and 925 SSR markers with each having a single amplicon in the cucumber and melon draft genome, respectively. Comparative analysis with these cross-species SSR markers revealed complicated mosaic patterns of syntenic blocks among the genomes of three species. In addition, genetic diversity analysis of 134 watermelon accessions with 32 highly informative SSR loci placed these lines into two groups with all accessions of C.lanatus var. citorides and three accessions of C. colocynthis clustered in one group and all accessions of C. lanatus var. lanatus and the remaining accessions of C. colocynthis

  20. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  1. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  2. In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

    NARCIS (Netherlands)

    Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

    2005-01-01

    A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all

  3. Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

    NARCIS (Netherlands)

    Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

    2016-01-01

    Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is

  4. IMG: the integrated microbial genomes database and comparative analysis system

    Science.gov (United States)

    Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Jacob, Biju; Huang, Jinghua; Williams, Peter; Huntemann, Marcel; Anderson, Iain; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

    2012-01-01

    The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMG's data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp). PMID:22194640

  5. Efficient population-scale variant analysis and prioritization with VAPr.

    Science.gov (United States)

    Birmingham, Amanda; Mark, Adam M; Mazzaferro, Carlo; Xu, Guorong; Fisch, Kathleen M

    2018-04-06

    With the growing availability of population-scale whole-exome and whole-genome sequencing, demand for reproducible, scalable variant analysis has spread within genomic research communities. To address this need, we introduce the Python package VAPr (Variant Analysis and Prioritization). VAPr leverages existing annotation tools ANNOVAR and MyVariant.info with MongoDB-based flexible storage and filtering functionality. It offers biologists and bioinformatics generalists easy-to-use and scalable analysis and prioritization of genomic variants from large cohort studies. VAPr is developed in Python and is available for free use and extension under the MIT License. An install package is available on PyPi at https://pypi.python.org/pypi/VAPr, while source code and extensive documentation are on GitHub at https://github.com/ucsd-ccbb/VAPr. kfisch@ucsd.edu.

  6. Genomic analysis of Xenopus organizer function

    Directory of Open Access Journals (Sweden)

    Suhai Sándor

    2006-06-01

    Full Text Available Abstract Background Studies of the Xenopus organizer have laid the foundation for our understanding of the conserved signaling pathways that pattern vertebrate embryos during gastrulation. The two primary activities of the organizer, BMP and Wnt inhibition, can regulate a spectrum of genes that pattern essentially all aspects of the embryo during gastrulation. As our knowledge of organizer signaling grows, it is imperative that we begin knitting together our gene-level knowledge into genome-level signaling models. The goal of this paper was to identify complete lists of genes regulated by different aspects of organizer signaling, thereby providing a deeper understanding of the genomic mechanisms that underlie these complex and fundamental signaling events. Results To this end, we ectopically overexpress Noggin and Dkk-1, inhibitors of the BMP and Wnt pathways, respectively, within ventral tissues. After isolating embryonic ventral halves at early and late gastrulation, we analyze the transcriptional response to these molecules within the generated ectopic organizers using oligonucleotide microarrays. An efficient statistical analysis scheme, combined with a new Gene Ontology biological process annotation of the Xenopus genome, allows reliable and faithful clustering of molecules based upon their roles during gastrulation. From this data, we identify new organizer-related expression patterns for 19 genes. Moreover, our data sub-divides organizer genes into separate head and trunk organizing groups, which each show distinct responses to Noggin and Dkk-1 activity during gastrulation. Conclusion Our data provides a genomic view of the cohorts of genes that respond to Noggin and Dkk-1 activity, allowing us to separate the role of each in organizer function. These patterns demonstrate a model where BMP inhibition plays a largely inductive role during early developmental stages, thereby initiating the suites of genes needed to pattern dorsal tissues

  7. Ethical considerations of research policy for personal genome analysis: the approach of the Genome Science Project in Japan.

    Science.gov (United States)

    Minari, Jusaku; Shirai, Tetsuya; Kato, Kazuto

    2014-12-01

    As evidenced by high-throughput sequencers, genomic technologies have recently undergone radical advances. These technologies enable comprehensive sequencing of personal genomes considerably more efficiently and less expensively than heretofore. These developments present a challenge to the conventional framework of biomedical ethics; under these changing circumstances, each research project has to develop a pragmatic research policy. Based on the experience with a new large-scale project-the Genome Science Project-this article presents a novel approach to conducting a specific policy for personal genome research in the Japanese context. In creating an original informed-consent form template for the project, we present a two-tiered process: making the draft of the template following an analysis of national and international policies; refining the draft template in conjunction with genome project researchers for practical application. Through practical use of the template, we have gained valuable experience in addressing challenges in the ethical review process, such as the importance of sharing details of the latest developments in genomics with members of research ethics committees. We discuss certain limitations of the conventional concept of informed consent and its governance system and suggest the potential of an alternative process using information technology.

  8. The complete mitochondrial genome of Gossypium hirsutum and evolutionary analysis of higher plant mitochondrial genomes.

    Science.gov (United States)

    Liu, Guozheng; Cao, Dandan; Li, Shuangshuang; Su, Aiguo; Geng, Jianing; Grover, Corrinne E; Hu, Songnian; Hua, Jinping

    2013-01-01

    Mitochondria are the main manufacturers of cellular ATP in eukaryotes. The plant mitochondrial genome contains large number of foreign DNA and repeated sequences undergone frequently intramolecular recombination. Upland Cotton (Gossypium hirsutum L.) is one of the main natural fiber crops and also an important oil-producing plant in the world. Sequencing of the cotton mitochondrial (mt) genome could be helpful for the evolution research of plant mt genomes. We utilized 454 technology for sequencing and combined with Fosmid library of the Gossypium hirsutum mt genome screening and positive clones sequencing and conducted a series of evolutionary analysis on Cycas taitungensis and 24 angiosperms mt genomes. After data assembling and contigs joining, the complete mitochondrial genome sequence of G. hirsutum was obtained. The completed G.hirsutum mt genome is 621,884 bp in length, and contained 68 genes, including 35 protein genes, four rRNA genes and 29 tRNA genes. Five gene clusters are found conserved in all plant mt genomes; one and four clusters are specifically conserved in monocots and dicots, respectively. Homologous sequences are distributed along the plant mt genomes and species closely related share the most homologous sequences. For species that have both mt and chloroplast genome sequences available, we checked the location of cp-like migration and found several fragments closely linked with mitochondrial genes. The G. hirsutum mt genome possesses most of the common characters of higher plant mt genomes. The existence of syntenic gene clusters, as well as the conservation of some intergenic sequences and genic content among the plant mt genomes suggest that evolution of mt genomes is consistent with plant taxonomy but independent among different species.

  9. Phylogenomic Analysis and Dynamic Evolution of Chloroplast Genomes in Salicaceae

    Directory of Open Access Journals (Sweden)

    Yuan Huang

    2017-06-01

    Full Text Available Chloroplast genomes of plants are highly conserved in both gene order and gene content. Analysis of the whole chloroplast genome is known to provide much more informative DNA sites and thus generates high resolution for plant phylogenies. Here, we report the complete chloroplast genomes of three Salix species in family Salicaceae. Phylogeny of Salicaceae inferred from complete chloroplast genomes is generally consistent with previous studies but resolved with higher statistical support. Incongruences of phylogeny, however, are observed in genus Populus, which most likely results from homoplasy. By comparing three Salix chloroplast genomes with the published chloroplast genomes of other Salicaceae species, we demonstrate that the synteny and length of chloroplast genomes in Salicaceae are highly conserved but experienced dynamic evolution among species. We identify seven positively selected chloroplast genes in Salicaceae, which might be related to the adaptive evolution of Salicaceae species. Comparative chloroplast genome analysis within the family also indicates that some chloroplast genes are lost or became pseudogenes, infer that the chloroplast genes horizontally transferred to the nucleus genome. Based on the complete nucleus genome sequences from two Salicaceae species, we remarkably identify that the entire chloroplast genome is indeed transferred and integrated to the nucleus genome in the individual of the reference genome of P. trichocarpa at least once. This observation, along with presence of the large nuclear plastid DNA (NUPTs and NUPTs-containing multiple chloroplast genes in their original order in the chloroplast genome, favors the DNA-mediated hypothesis of organelle to nucleus DNA transfer. Overall, the phylogenomic analysis using chloroplast complete genomes clearly elucidates the phylogeny of Salicaceae. The identification of positively selected chloroplast genes and dynamic chloroplast-to-nucleus gene transfers in

  10. Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

    Science.gov (United States)

    Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

    2013-01-01

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

  11. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

    Science.gov (United States)

    Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

    2013-07-16

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  12. Millstone: software for multiplex microbial genome analysis and engineering.

    Science.gov (United States)

    Goodman, Daniel B; Kuznetsov, Gleb; Lajoie, Marc J; Ahern, Brian W; Napolitano, Michael G; Chen, Kevin Y; Chen, Changping; Church, George M

    2017-05-25

    Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

  13. SWAP-Assembler 2: Optimization of De Novo Genome Assembler at Large Scale

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Jintao; Seo, Sangmin; Balaji, Pavan; Wei, Yanjie; Wang, Bingqiang; Feng, Shengzhong

    2016-08-16

    In this paper, we analyze and optimize the most time-consuming steps of the SWAP-Assembler, a parallel genome assembler, so that it can scale to a large number of cores for huge genomes with the size of sequencing data ranging from terabyes to petabytes. According to the performance analysis results, the most time-consuming steps are input parallelization, k-mer graph construction, and graph simplification (edge merging). For the input parallelization, the input data is divided into virtual fragments with nearly equal size, and the start position and end position of each fragment are automatically separated at the beginning of the reads. In k-mer graph construction, in order to improve the communication efficiency, the message size is kept constant between any two processes by proportionally increasing the number of nucleotides to the number of processes in the input parallelization step for each round. The memory usage is also decreased because only a small part of the input data is processed in each round. With graph simplification, the communication protocol reduces the number of communication loops from four to two loops and decreases the idle communication time. The optimized assembler is denoted as SWAP-Assembler 2 (SWAP2). In our experiments using a 1000 Genomes project dataset of 4 terabytes (the largest dataset ever used for assembling) on the supercomputer Mira, the results show that SWAP2 scales to 131,072 cores with an efficiency of 40%. We also compared our work with both the HipMER assembler and the SWAP-Assembler. On the Yanhuang dataset of 300 gigabytes, SWAP2 shows a 3X speedup and 4X better scalability compared with the HipMer assembler and is 45 times faster than the SWAP-Assembler. The SWAP2 software is available at https://sourceforge.net/projects/swapassembler.

  14. A comparative genome analysis of Cercospora sojina with other members of the pathogen genus Mycosphaerella on different plant hosts

    Directory of Open Access Journals (Sweden)

    Fanchang Zeng

    2017-09-01

    Full Text Available Fungi are the causal agents of many of the world's most serious plant diseases causing disastrous consequences for large-scale agricultural production. Pathogenicity genomic basis is complex in fungi as multicellular eukaryotic pathogens. Here, we report the genome sequence of C. sojina, and comparative genome analysis with plant pathogen members of the genus Mycosphaerella (Zymoseptoria. tritici (synonyms M. graminicola, M. pini, M. populorum and M. fijiensis - pathogens of wheat, pine, poplar and banana, respectively. Synteny or collinearity was limited between genomes of major Mycosphaerella pathogens. Comparative analysis with these related pathogen genomes indicated distinct genome-wide repeat organization features. It suggests repetitive elements might be responsible for considerable evolutionary genomic changes. These results reveal the background of genomic differences and similarities between Dothideomycete species. Wide diversity as well as conservation on genome features forms the potential genomic basis of the pathogen specialization, such as pathogenicity to woody vs. herbaceous hosts. Through comparative genome analysis among five Dothideomycete species, our results have shed light on the genome features of these related fungi species. It provides insight for understanding the genomic basis of fungal pathogenicity and disease resistance in the crop hosts.

  15. Large-scale chromatin immunoprecipitation with promoter sequence microarray analysis of the interaction of the NSs protein of Rift Valley fever virus with regulatory DNA regions of the host genome.

    Science.gov (United States)

    Benferhat, Rima; Josse, Thibaut; Albaud, Benoit; Gentien, David; Mansuroglu, Zeyni; Marcato, Vasco; Souès, Sylvie; Le Bonniec, Bernard; Bouloy, Michèle; Bonnefoy, Eliette

    2012-10-01

    Rift Valley fever virus (RVFV) is a highly pathogenic Phlebovirus that infects humans and ruminants. Initially confined to Africa, RVFV has spread outside Africa and presently represents a high risk to other geographic regions. It is responsible for high fatality rates in sheep and cattle. In humans, RVFV can induce hepatitis, encephalitis, retinitis, or fatal hemorrhagic fever. The nonstructural NSs protein that is the major virulence factor is found in the nuclei of infected cells where it associates with cellular transcription factors and cofactors. In previous work, we have shown that NSs interacts with the promoter region of the beta interferon gene abnormally maintaining the promoter in a repressed state. In this work, we performed a genome-wide analysis of the interactions between NSs and the host genome using a genome-wide chromatin immunoprecipitation combined with promoter sequence microarray, the ChIP-on-chip technique. Several cellular promoter regions were identified as significantly interacting with NSs, and the establishment of NSs interactions with these regions was often found linked to deregulation of expression of the corresponding genes. Among annotated NSs-interacting genes were present not only genes regulating innate immunity and inflammation but also genes regulating cellular pathways that have not yet been identified as targeted by RVFV. Several of these pathways, such as cell adhesion, axonal guidance, development, and coagulation were closely related to RVFV-induced disorders. In particular, we show in this work that NSs targeted and modified the expression of genes coding for coagulation factors, demonstrating for the first time that this hemorrhagic virus impairs the host coagulation cascade at the transcriptional level.

  16. Direct-to-consumer genomics on the scales of autonomy

    Science.gov (United States)

    Vayena, Effy

    2015-01-01

    Direct-to-consumer (DTC) genetic services have generated enormous controversy from their first emergence. A dramatic recent manifestation of this is the Food and Drug Administration's (FDA) cease and desist order against 23andMe, the leading provider in the market. Critics have argued for the restrictive regulation of such services, and even their prohibition, on the grounds of the harm they pose to consumers. Their advocates, by contrast, defend them as a means of enhancing the autonomy of those same consumers. Autonomy emerges as a key battle-field in this debate, because many of the ‘harm’ arguments can be interpreted as identifying threats to autonomy. This paper assesses whether DTC genomic services are a threat to, or instead, an enhancement of, personal autonomy. It deploys Joseph Raz's account of personal autonomy, with its emphasis on choice from a range of valuable options. It then seeks to counter claims that DTC genomics threatens autonomy because it involves manipulation in contravention of consumers’ independence or because it does not generate valuable options which can be meaningfully engaged with by consumers. It is stressed that the value of the options generated by DTC genomics should not be judged exclusively from the perspective of medical actionability, but should take into consideration plural utilities. Finally, the paper ends by broaching policy recommendations, suggesting that there is a strong autonomy-based argument for permitting DTC genomic services, and that the key question is the nature of the regulatory conditions under which they should be permitted. The discussion of autonomy in this paper helps illuminate some of these conditions. PMID:24797610

  17. Virtual Northern analysis of the human genome.

    Directory of Open Access Journals (Sweden)

    Evan H Hurowitz

    2007-05-01

    Full Text Available We applied the Virtual Northern technique to human brain mRNA to systematically measure human mRNA transcript lengths on a genome-wide scale.We used separation by gel electrophoresis followed by hybridization to cDNA microarrays to measure 8,774 mRNA transcript lengths representing at least 6,238 genes at high (>90% confidence. By comparing these transcript lengths to the Refseq and H-Invitational full-length cDNA databases, we found that nearly half of our measurements appeared to represent novel transcript variants. Comparison of length measurements determined by hybridization to different cDNAs derived from the same gene identified clones that potentially correspond to alternative transcript variants. We observed a close linear relationship between ORF and mRNA lengths in human mRNAs, identical in form to the relationship we had previously identified in yeast. Some functional classes of protein are encoded by mRNAs whose untranslated regions (UTRs tend to be longer or shorter than average; these functional classes were similar in both human and yeast.Human transcript diversity is extensive and largely unannotated. Our length dataset can be used as a new criterion for judging the completeness of cDNAs and annotating mRNA sequences. Similar relationships between the lengths of the UTRs in human and yeast mRNAs and the functions of the proteins they encode suggest that UTR sequences serve an important regulatory role among eukaryotes.

  18. Virtual Northern analysis of the human genome.

    Science.gov (United States)

    Hurowitz, Evan H; Drori, Iddo; Stodden, Victoria C; Donoho, David L; Brown, Patrick O

    2007-05-23

    We applied the Virtual Northern technique to human brain mRNA to systematically measure human mRNA transcript lengths on a genome-wide scale. We used separation by gel electrophoresis followed by hybridization to cDNA microarrays to measure 8,774 mRNA transcript lengths representing at least 6,238 genes at high (>90%) confidence. By comparing these transcript lengths to the Refseq and H-Invitational full-length cDNA databases, we found that nearly half of our measurements appeared to represent novel transcript variants. Comparison of length measurements determined by hybridization to different cDNAs derived from the same gene identified clones that potentially correspond to alternative transcript variants. We observed a close linear relationship between ORF and mRNA lengths in human mRNAs, identical in form to the relationship we had previously identified in yeast. Some functional classes of protein are encoded by mRNAs whose untranslated regions (UTRs) tend to be longer or shorter than average; these functional classes were similar in both human and yeast. Human transcript diversity is extensive and largely unannotated. Our length dataset can be used as a new criterion for judging the completeness of cDNAs and annotating mRNA sequences. Similar relationships between the lengths of the UTRs in human and yeast mRNAs and the functions of the proteins they encode suggest that UTR sequences serve an important regulatory role among eukaryotes.

  19. SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

    Directory of Open Access Journals (Sweden)

    Davies Jonathan J

    2006-12-01

    Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.

  20. Barcode server: a visualization-based genome analysis system.

    Directory of Open Access Journals (Sweden)

    Fenglou Mao

    Full Text Available We have previously developed a computational method for representing a genome as a barcode image, which makes various genomic features visually apparent. We have demonstrated that this visual capability has made some challenging genome analysis problems relatively easy to solve. We have applied this capability to a number of challenging problems, including (a identification of horizontally transferred genes, (b identification of genomic islands with special properties and (c binning of metagenomic sequences, and achieved highly encouraging results. These application results inspired us to develop this barcode-based genome analysis server for public service, which supports the following capabilities: (a calculation of the k-mer based barcode image for a provided DNA sequence; (b detection of sequence fragments in a given genome with distinct barcodes from those of the majority of the genome, (c clustering of provided DNA sequences into groups having similar barcodes; and (d homology-based search using Blast against a genome database for any selected genomic regions deemed to have interesting barcodes. The barcode server provides a job management capability, allowing processing of a large number of analysis jobs for barcode-based comparative genome analyses. The barcode server is accessible at http://csbl1.bmb.uga.edu/Barcode.

  1. A Genomics Approach to Tumor Gemome Analysis

    National Research Council Canada - National Science Library

    Collins, Colin

    2002-01-01

    Genomes of solid tumors are often highly rearranged and these rearrangements promote cancer progression through disruption of genes mediating immortality, survival, metastasis, and resistance to therapy...

  2. RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

    Science.gov (United States)

    Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

    2013-11-01

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

  3. Pathway and network analysis of cancer genomes

    DEFF Research Database (Denmark)

    Creixell, Pau; Reimand, Jueri; Haider, Syed

    2015-01-01

    Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been...

  4. GENOME ANALYSIS OF BURKHOLDERIA CEPACIA AC1100

    Science.gov (United States)

    Burkholderia cepacia is an important organism in bioremediation of environmental pollutants and it is also of increasing interest as a human pathogen. The genomic organization of B. cepacia is being studied in order to better understand its unusual adaptive capacity and genome pl...

  5. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...

  6. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  7. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  8. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. GenomePeek—an online tool for prokaryotic genome and metagenome analysis

    Directory of Open Access Journals (Sweden)

    Katelyn McNair

    2015-06-01

    Full Text Available As more and more prokaryotic sequencing takes place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping error rates low, as well as offering unique data visualization options.

  10. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  11. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Science.gov (United States)

    De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

    2014-01-01

    The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  12. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  13. Dimensional analysis, scaling and fractals

    International Nuclear Information System (INIS)

    Timm, L.C.; Reichardt, K.; Oliveira Santos Bacchi, O.

    2004-01-01

    Dimensional analysis refers to the study of the dimensions that characterize physical entities, like mass, force and energy. Classical mechanics is based on three fundamental entities, with dimensions MLT, the mass M, the length L and the time T. The combination of these entities gives rise to derived entities, like volume, speed and force, of dimensions L 3 , LT -1 , MLT -2 , respectively. In other areas of physics, four other fundamental entities are defined, among them the temperature θ and the electrical current I. The parameters that characterize physical phenomena are related among themselves by laws, in general of quantitative nature, in which they appear as measures of the considered physical entities. The measure of an entity is the result of its comparison with another one, of the same type, called unit. Maps are also drawn in scale, for example, in a scale of 1:10,000, 1 cm 2 of paper can represent 10,000 m 2 in the field. Entities that differ in scale cannot be compared in a simple way. Fractal geometry, in contrast to the Euclidean geometry, admits fractional dimensions. The term fractal is defined in Mandelbrot (1982) as coming from the Latin fractus, derived from frangere which signifies to break, to form irregular fragments. The term fractal is opposite to the term algebra (from the Arabic: jabara) which means to join, to put together the parts. For Mandelbrot, fractals are non topologic objects, that is, objects which have as their dimension a real, non integer number, which exceeds the topologic dimension. For the topologic objects, or Euclidean forms, the dimension is an integer (0 for the point, 1 for a line, 2 for a surface, and 3 for a volume). The fractal dimension of Mandelbrot is a measure of the degree of irregularity of the object under consideration. It is related to the speed by which the estimate of the measure of an object increases as the measurement scale decreases. An object normally taken as uni-dimensional, like a piece of a

  14. Genomic sequence around butterfly wing development genes: annotation and comparative analysis.

    Directory of Open Access Journals (Sweden)

    Inês C Conceição

    Full Text Available BACKGROUND: Analysis of genomic sequence allows characterization of genome content and organization, and access beyond gene-coding regions for identification of functional elements. BAC libraries, where relatively large genomic regions are made readily available, are especially useful for species without a fully sequenced genome and can increase genomic coverage of phylogenetic and biological diversity. For example, no butterfly genome is yet available despite the unique genetic and biological properties of this group, such as diversified wing color patterns. The evolution and development of these patterns is being studied in a few target species, including Bicyclus anynana, where a whole-genome BAC library allows targeted access to large genomic regions. METHODOLOGY/PRINCIPAL FINDINGS: We characterize ∼1.3 Mb of genomic sequence around 11 selected genes expressed in B. anynana developing wings. Extensive manual curation of in silico predictions, also making use of a large dataset of expressed genes for this species, identified repetitive elements and protein coding sequence, and highlighted an expansion of Alcohol dehydrogenase genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes. CONCLUSIONS: The general properties and organization of the available B. anynana genomic sequence are similar to the lepidopteran reference, despite the more than 140 MY divergence. Our results lay the groundwork for further studies of new interesting findings in relation to both coding and non-coding sequence: 1 the Alcohol dehydrogenase expansion with higher similarity between the five tandemly-repeated B. anynana paralogs than with the corresponding B. mori orthologs, and 2 the high

  15. Analysis of intra-genomic GC content homogeneity within prokaryotes

    DEFF Research Database (Denmark)

    Bohlin, J; Snipen, L; Hardy, S.P.

    2010-01-01

    the GC content varies within microbial genomes to assess whether this property can be associated with certain biological functions related to the organism's environment and phylogeny. We utilize a new quantity GCVAR, the intra-genomic GC content variability with respect to the average GC content......Bacterial genomes possess varying GC content (total guanines (Gs) and cytosines (Cs) per total of the four bases within the genome) but within a given genome, GC content can vary locally along the chromosome, with some regions significantly more or less GC rich than on average. We have examined how...... both aerobic and facultative microbes. Although an association has previously been found between mean genomic GC content and oxygen requirement, our analysis suggests that no such association exits when phylogenetic bias is accounted for. A significant association between GCVAR and mean GC content...

  16. Creation and genomic analysis of irradiation hybrids in Populus

    Science.gov (United States)

    Matthew S. Zinkgraf; K. Haiby; M.C. Lieberman; L. Comai; I.M. Henry; Andrew Groover

    2016-01-01

    Establishing efficient functional genomic systems for creating and characterizing genetic variation in forest trees is challenging. Here we describe protocols for creating novel gene-dosage variation in Populus through gamma-irradiation of pollen, followed by genomic analysis to identify chromosomal regions that have been deleted or inserted in...

  17. Genome-scale metabolic models as platforms for strain design and biological discovery.

    Science.gov (United States)

    Mienda, Bashir Sajo

    2017-07-01

    Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

  18. A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

    Directory of Open Access Journals (Sweden)

    Sheina B. Sim

    2017-06-01

    Full Text Available Genetic sexing strains (GSS used in sterile insect technique (SIT programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp, also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera.

  19. Rapid prototyping of microbial cell factories via genome-scale engineering.

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2015-11-15

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2014-01-01

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

  1. Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

    Science.gov (United States)

    Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

  2. Genome-scale consequences of cofactor balancing in engineered pentose utilization pathways in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Amit Ghosh

    Full Text Available Biofuels derived from lignocellulosic biomass offer promising alternative renewable energy sources for transportation fuels. Significant effort has been made to engineer Saccharomyces cerevisiae to efficiently ferment pentose sugars such as D-xylose and L-arabinose into biofuels such as ethanol through heterologous expression of the fungal D-xylose and L-arabinose pathways. However, one of the major bottlenecks in these fungal pathways is that the cofactors are not balanced, which contributes to inefficient utilization of pentose sugars. We utilized a genome-scale model of S. cerevisiae to predict the maximal achievable growth rate for cofactor balanced and imbalanced D-xylose and L-arabinose utilization pathways. Dynamic flux balance analysis (DFBA was used to simulate batch fermentation of glucose, D-xylose, and L-arabinose. The dynamic models and experimental results are in good agreement for the wild type and for the engineered D-xylose utilization pathway. Cofactor balancing the engineered D-xylose and L-arabinose utilization pathways simulated an increase in ethanol batch production of 24.7% while simultaneously reducing the predicted substrate utilization time by 70%. Furthermore, the effects of cofactor balancing the engineered pentose utilization pathways were evaluated throughout the genome-scale metabolic network. This work not only provides new insights to the global network effects of cofactor balancing but also provides useful guidelines for engineering a recombinant yeast strain with cofactor balanced engineered pathways that efficiently co-utilizes pentose and hexose sugars for biofuels production. Experimental switching of cofactor usage in enzymes has been demonstrated, but is a time-consuming effort. Therefore, systems biology models that can predict the likely outcome of such strain engineering efforts are highly useful for motivating which efforts are likely to be worth the significant time investment.

  3. Broad genomic and transcriptional analysis reveals a highly derived genome in dinoflagellate mitochondria

    Directory of Open Access Journals (Sweden)

    Keeling Patrick J

    2007-09-01

    Full Text Available Abstract Background Dinoflagellates comprise an ecologically significant and diverse eukaryotic phylum that is sister to the phylum containing apicomplexan endoparasites. The mitochondrial genome of apicomplexans is uniquely reduced in gene content and size, encoding only three proteins and two ribosomal RNAs (rRNAs within a highly compacted 6 kb DNA. Dinoflagellate mitochondrial genomes have been comparatively poorly studied: limited available data suggest some similarities with apicomplexan mitochondrial genomes but an even more radical type of genomic organization. Here, we investigate structure, content and expression of dinoflagellate mitochondrial genomes. Results From two dinoflagellates, Crypthecodinium cohnii and Karlodinium micrum, we generated over 42 kb of mitochondrial genomic data that indicate a reduced gene content paralleling that of mitochondrial genomes in apicomplexans, i.e., only three protein-encoding genes and at least eight conserved components of the highly fragmented large and small subunit rRNAs. Unlike in apicomplexans, dinoflagellate mitochondrial genes occur in multiple copies, often as gene fragments, and in numerous genomic contexts. Analysis of cDNAs suggests several novel aspects of dinoflagellate mitochondrial gene expression. Polycistronic transcripts were found, standard start codons are absent, and oligoadenylation occurs upstream of stop codons, resulting in the absence of termination codons. Transcripts of at least one gene, cox3, are apparently trans-spliced to generate full-length mRNAs. RNA substitutional editing, a process previously identified for mRNAs in dinoflagellate mitochondria, is also implicated in rRNA expression. Conclusion The dinoflagellate mitochondrial genome shares the same gene complement and fragmentation of rRNA genes with its apicomplexan counterpart. However, it also exhibits several unique characteristics. Most notable are the expansion of gene copy numbers and their arrangements

  4. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander; Mularoni, Loris; Cope, Leslie M.; Medvedeva, Yulia; Mironov, Andrey A.; Makeev, Vsevolod J.; Wheelan, Sarah J.

    2012-01-01

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  5. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander

    2012-05-31

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  6. Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes.

    Science.gov (United States)

    Prabha, Ratna; Singh, Dhananjaya P; Sinha, Swati; Ahmad, Khurshid; Rai, Anil

    2017-04-01

    With the increasing accumulation of genomic sequence information of prokaryotes, the study of codon usage bias has gained renewed attention. The purpose of this study was to examine codon selection pattern within and across cyanobacterial species belonging to diverse taxonomic orders and habitats. We performed detailed comparative analysis of cyanobacterial genomes with respect to codon bias. Our analysis reflects that in cyanobacterial genomes, A- and/or T-ending codons were used predominantly in the genes whereas G- and/or C-ending codons were largely avoided. Variation in the codon context usage of cyanobacterial genes corresponded to the clustering of cyanobacteria as per their GC content. Analysis of codon adaptation index (CAI) and synonymous codon usage order (SCUO) revealed that majority of genes are associated with low codon bias. Codon selection pattern in cyanobacterial genomes reflected compositional constraints as major influencing factor. It is also identified that although, mutational constraint may play some role in affecting codon usage bias in cyanobacteria, compositional constraint in terms of genomic GC composition coupled with environmental factors affected codon selection pattern in cyanobacterial genomes. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  8. RESEARCH NOTE Genome-based exome-sequencing analysis ...

    Indian Academy of Sciences (India)

    Navya

    2017-02-22

    Feb 22, 2017 ... Genome-based exome-sequencing analysis identifies GYG1, DIS3L, DDRGK1 genes ... Cardiology Division, Department of Internal Medicine, Severance .... with p values of <0.05 byanalyzing differences in allele distribution.

  9. Genome inventory and analysis of nuclear hormone receptors in ...

    Indian Academy of Sciences (India)

    Prakash

    2006-12-20

    Dec 20, 2006 ... progestins, as well as lipids, cholesterol metabolites, and. Genome ... Gene structure analysis shows strong conservation of exon structures among orthologoues. ..... earlier subfamily classification of NRs (Nuclear Receptors.

  10. Human · mouse genome analysis and radiation biology. Proceedings

    International Nuclear Information System (INIS)

    Hori, Tada-aki

    1994-03-01

    This issue is the collection of the papers presented at the 25th NIRS symposium on Human, Mouse Genome Analysis and Radiation Biology. The 14 of the presented papers are indexed individually. (J.P.N.)

  11. Comparative analysis of rosaceous genomes and the reconstruction of a putative ancestral genome for the family.

    Science.gov (United States)

    Illa, Eudald; Sargent, Daniel J; Lopez Girona, Elena; Bushakra, Jill; Cestaro, Alessandro; Crowhurst, Ross; Pindo, Massimo; Cabrera, Antonio; van der Knaap, Esther; Iezzoni, Amy; Gardiner, Susan; Velasco, Riccardo; Arús, Pere; Chagné, David; Troggio, Michela

    2011-01-12

    Comparative genome mapping studies in Rosaceae have been conducted until now by aligning genetic maps within the same genus, or closely related genera and using a limited number of common markers. The growing body of genomics resources and sequence data for both Prunus and Fragaria permits detailed comparisons between these genera and the recently released Malus × domestica genome sequence. We generated a comparative analysis using 806 molecular markers that are anchored genetically to the Prunus and/or Fragaria reference maps, and physically to the Malus genome sequence. Markers in common for Malus and Prunus, and Malus and Fragaria, respectively were 784 and 148. The correspondence between marker positions was high and conserved syntenic blocks were identified among the three genera in the Rosaceae. We reconstructed a proposed ancestral genome for the Rosaceae. A genome containing nine chromosomes is the most likely candidate for the ancestral Rosaceae progenitor. The number of chromosomal translocations observed between the three genera investigated was low. However, the number of inversions identified among Malus and Prunus was much higher than any reported genome comparisons in plants, suggesting that small inversions have played an important role in the evolution of these two genera or of the Rosaceae.

  12. Comparative analysis of rosaceous genomes and the reconstruction of a putative ancestral genome for the family

    Directory of Open Access Journals (Sweden)

    Velasco Riccardo

    2011-01-01

    Full Text Available Abstract Background Comparative genome mapping studies in Rosaceae have been conducted until now by aligning genetic maps within the same genus, or closely related genera and using a limited number of common markers. The growing body of genomics resources and sequence data for both Prunus and Fragaria permits detailed comparisons between these genera and the recently released Malus × domestica genome sequence. Results We generated a comparative analysis using 806 molecular markers that are anchored genetically to the Prunus and/or Fragaria reference maps, and physically to the Malus genome sequence. Markers in common for Malus and Prunus, and Malus and Fragaria, respectively were 784 and 148. The correspondence between marker positions was high and conserved syntenic blocks were identified among the three genera in the Rosaceae. We reconstructed a proposed ancestral genome for the Rosaceae. Conclusions A genome containing nine chromosomes is the most likely candidate for the ancestral Rosaceae progenitor. The number of chromosomal translocations observed between the three genera investigated was low. However, the number of inversions identified among Malus and Prunus was much higher than any reported genome comparisons in plants, suggesting that small inversions have played an important role in the evolution of these two genera or of the Rosaceae.

  13. Comparative Pan-Genome Analysis of Piscirickettsia salmonis Reveals Genomic Divergences within Genogroups

    Directory of Open Access Journals (Sweden)

    Guillermo Nourdin-Galindo

    2017-10-01

    Full Text Available Piscirickettsia salmonis is the etiological agent of salmonid rickettsial septicemia, a disease that seriously affects the salmonid industry. Despite efforts to genomically characterize P. salmonis, functional information on the life cycle, pathogenesis mechanisms, diagnosis, treatment, and control of this fish pathogen remain lacking. To address this knowledge gap, the present study conducted an in silico pan-genome analysis of 19 P. salmonis strains from distinct geographic locations and genogroups. Results revealed an expected open pan-genome of 3,463 genes and a core-genome of 1,732 genes. Two marked genogroups were identified, as confirmed by phylogenetic and phylogenomic relationships to the LF-89 and EM-90 reference strains, as well as by assessments of genomic structures. Different structural configurations were found for the six identified copies of the ribosomal operon in the P. salmonis genome, indicating translocation throughout the genetic material. Chromosomal divergences in genomic localization and quantity of genetic cassettes were also found for the Dot/Icm type IVB secretion system. To determine divergences between core-genomes, additional pan-genome descriptions were compiled for the so-termed LF and EM genogroups. Open pan-genomes composed of 2,924 and 2,778 genes and core-genomes composed of 2,170 and 2,228 genes were respectively found for the LF and EM genogroups. The core-genomes were functionally annotated using the Gene Ontology, KEGG, and Virulence Factor databases, revealing the presence of several shared groups of genes related to basic function of intracellular survival and bacterial pathogenesis. Additionally, the specific pan-genomes for the LF and EM genogroups were defined, resulting in the identification of 148 and 273 exclusive proteins, respectively. Notably, specific virulence factors linked to adherence, colonization, invasion factors, and endotoxins were established. The obtained data suggest that these

  14. Data on genome analysis of Bacillus velezensis LS69.

    Science.gov (United States)

    Liu, Guoqiang; Kong, Yingying; Fan, Yajing; Geng, Ce; Peng, Donghai; Sun, Ming

    2017-08-01

    The data presented in this article are related to the published entitled "Whole-genome sequencing of Bacillus velezensis LS69, a strain with a broad inhibitory spectrum against pathogenic bacteria" (Liu et al., 2017) [1]. Genome analysis revealed B. velezensis LS69 has a good potential for biocontrol and plant growth promotion. This article provides an extended analysis of the genetic islands, core genes and amylolysin loci of B. velezensis LS69.

  15. Data on genome analysis of Bacillus velezensis LS69

    OpenAIRE

    Liu, Guoqiang; Kong, Yingying; Fan, Yajing; Geng, Ce; Peng, Donghai; Sun, Ming

    2017-01-01

    The data presented in this article are related to the published entitled “Whole-genome sequencing of Bacillus velezensis LS69, a strain with a broad inhibitory spectrum against pathogenic bacteria” (Liu et al., 2017) [1]. Genome analysis revealed B. velezensis LS69 has a good potential for biocontrol and plant growth promotion. This article provides an extended analysis of the genetic islands, core genes and amylolysin loci of B. velezensis LS69.

  16. Data on genome analysis of Bacillus velezensis LS69

    Directory of Open Access Journals (Sweden)

    Guoqiang Liu

    2017-08-01

    Full Text Available The data presented in this article are related to the published entitled “Whole-genome sequencing of Bacillus velezensis LS69, a strain with a broad inhibitory spectrum against pathogenic bacteria” (Liu et al., 2017 [1]. Genome analysis revealed B. velezensis LS69 has a good potential for biocontrol and plant growth promotion. This article provides an extended analysis of the genetic islands, core genes and amylolysin loci of B. velezensis LS69.

  17. Genomic Analysis of Complex Microbial Communities in Wounds

    Science.gov (United States)

    2012-01-01

    Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no... permutation -based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and...coli. Antibiotics, bacteria, community analysis , diabetes, pyrosequencing, wound, wound therapy, 16S rRNA gene Genomic Analysis of Complex

  18. Mycobacterial species as case-study of comparative genome analysis.

    Science.gov (United States)

    Zakham, F; Belayachi, L; Ussery, D; Akrim, M; Benjouad, A; El Aouad, R; Ennaji, M M

    2011-02-08

    The genus Mycobacterium represents more than 120 species including important pathogens of human and cause major public health problems and illnesses. Further, with more than 100 genome sequences from this genus, comparative genome analysis can provide new insights for better understanding the evolutionary events of these species and improving drugs, vaccines, and diagnostics tools for controlling Mycobacterial diseases. In this present study we aim to outline a comparative genome analysis of fourteen Mycobacterial genomes: M. avium subsp. paratuberculosis K—10, M. bovis AF2122/97, M. bovis BCG str. Pasteur 1173P2, M. leprae Br4923, M. marinum M, M. sp. KMS, M. sp. MCS, M. tuberculosis CDC1551, M. tuberculosis F11, M. tuberculosis H37Ra, M. tuberculosis H37Rv, M. tuberculosis KZN 1435 , M. ulcerans Agy99,and M. vanbaalenii PYR—1, For this purpose a comparison has been done based on their length of genomes, GC content, number of genes in different data bases (Genbank, Refseq, and Prodigal). The BLAST matrix of these genomes has been figured to give a lot of information about the similarity between species in a simple scheme. As a result of multiple genome analysis, the pan and core genome have been defined for twelve Mycobacterial species. We have also introduced the genome atlas of the reference strain M. tuberculosis H37Rv which can give a good overview of this genome. And for examining the phylogenetic relationships among these bacteria, a phylogenic tree has been constructed from 16S rRNA gene for tuberculosis and non tuberculosis Mycobacteria to understand the evolutionary events of these species.

  19. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

  20. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

    Science.gov (United States)

    McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

    2012-05-14

    Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  1. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    King, Zachary A.; Lu, Justin; Dräger, Andreas

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

  2. Experience from large scale use of the EuroGenomics custom SNP chip in cattle

    DEFF Research Database (Denmark)

    Boichard, Didier A; Boussaha, Mekki; Capitan, Aurélien

    2018-01-01

    This article presents the strategy to evaluate candidate mutations underlying QTL or responsible for genetic defects, based upon the design and large-scale use of the Eurogenomics custom SNP chip set up for bovine genomic selection. Some variants under study originated from mapping genetic defect...

  3. Applied bioinformatics: Genome annotation and transcriptome analysis

    DEFF Research Database (Denmark)

    Gupta, Vikas

    agricultural and biological importance. Its capacity to form symbiotic relationships with rhizobia and microrrhizal fungi has fascinated researchers for years. Lotus has a small genome of approximately 470 Mb and a short life cycle of 2 to 3 months, which has made Lotus a model legume plant for many molecular...

  4. Comparative genome analysis of trypanotolerance QTL | Nganga ...

    African Journals Online (AJOL)

    Homologous sequences were used in the definition of synteny relationships and subsequent identification of the shared disease response genes. The homologous genes within the human genome were then identified and aligned to the bovine radiation hybrid map in order to identify the mouse/bovine homologous regions.

  5. DivStat: a user-friendly tool for single nucleotide polymorphism analysis of genomic diversity.

    Directory of Open Access Journals (Sweden)

    Inês Soares

    Full Text Available Recent developments have led to an enormous increase of publicly available large genomic data, including complete genomes. The 1000 Genomes Project was a major contributor, releasing the results of sequencing a large number of individual genomes, and allowing for a myriad of large scale studies on human genetic variation. However, the tools currently available are insufficient when the goal concerns some analyses of data sets encompassing more than hundreds of base pairs and when considering haplotype sequences of single nucleotide polymorphisms (SNPs. Here, we present a new and potent tool to deal with large data sets allowing the computation of a variety of summary statistics of population genetic data, increasing the speed of data analysis.

  6. Genome analysis methods - PGDBj Registered plant list, Marker list, QTL list, Plant DB link & Genome analysis methods | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us PGDBj Registered plant list, Marker list, QTL list, Plant DB link & Genome analysis methods Genome analysis... methods Data detail Data name Genome analysis methods DOI 10.18908/lsdba.nbdc01194-01-005 De...scription of data contents The current status and related information of the genomic analysis about each org...anism (March, 2014). In the case of organisms carried out genomic analysis, the d...e File name: pgdbj_dna_marker_linkage_map_genome_analysis_methods_en.zip File URL: ftp://ftp.biosciencedbc.j

  7. Rare and common regulatory variation in population-scale sequenced human genomes.

    Directory of Open Access Journals (Sweden)

    Stephen B Montgomery

    2011-07-01

    Full Text Available Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.

  8. Comparative analysis of the mitochondrial genomes in gastropods

    International Nuclear Information System (INIS)

    Arquez, Moises; Uribe, Juan Esteban; Castro, Lyda Raquel

    2012-01-01

    In this work we presented a comparative analysis of the mitochondrial genomes in gastropods. Nucleotide and amino acids composition was calculated and a comparative visual analysis of the start and termination codons was performed. The organization of the genome was compared calculating the number of intergenic sequences, the location of the genes and the number of reorganized genes (breakpoints) in comparison with the sequence that is presumed to be ancestral for the group. In order to calculate variations in the rates of molecular evolution within the group, the relative rate test was performed. In spite of the differences in the size of the genomes, the amino acids number is conserved. The nucleotide and amino acid composition is similar between Vetigastropoda, Ceanogastropoda and Neritimorpha in comparison to Heterobranchia and Patellogastropoda. The mitochondrial genomes of the group are very compact with few intergenic sequences, the only exception is the genome of Patellogastropoda with 26,828 bp. Start codons of the Heterobranchia and Patellogastropoda are very variable and there is also an increase in genome rearrangements for these two groups. Generally, the hypothesis of constant rates of molecular evolution between the groups is rejected, except when the genomes of Caenogastropoda and Vetigastropoda are compared.

  9. MIPS: analysis and annotation of proteins from whole genomes.

    Science.gov (United States)

    Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

    2004-01-01

    The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

  10. A Mitochondrial Genome of Rhyparochromidae (Hemiptera: Heteroptera) and a Comparative Analysis of Related Mitochondrial Genomes.

    Science.gov (United States)

    Li, Teng; Yang, Jie; Li, Yinwan; Cui, Ying; Xie, Qiang; Bu, Wenjun; Hillis, David M

    2016-10-19

    The Rhyparochromidae, the largest family of Lygaeoidea, encompasses more than 1,850 described species, but no mitochondrial genome has been sequenced to date. Here we describe the first mitochondrial genome for Rhyparochromidae: a complete mitochondrial genome of Panaorus albomaculatus (Scott, 1874). This mitochondrial genome is comprised of 16,345 bp, and contains the expected 37 genes and control region. The majority of the control region is made up of a large tandem-repeat region, which has a novel pattern not previously observed in other insects. The tandem-repeats region of P. albomaculatus consists of 53 tandem duplications (including one partial repeat), which is the largest number of tandem repeats among all the known insect mitochondrial genomes. Slipped-strand mispairing during replication is likely to have generated this novel pattern of tandem repeats. Comparative analysis of tRNA gene families in sequenced Pentatomomorpha and Lygaeoidea species shows that the pattern of nucleotide conservation is markedly higher on the J-strand. Phylogenetic reconstruction based on mitochondrial genomes suggests that Rhyparochromidae is not the sister group to all the remaining Lygaeoidea, and supports the monophyly of Lygaeoidea.

  11. Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

    Directory of Open Access Journals (Sweden)

    Daugherty Sean

    2009-09-01

    Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

  12. COGNAT: a web server for comparative analysis of genomic neighborhoods.

    Science.gov (United States)

    Klimchuk, Olesya I; Konovalov, Kirill A; Perekhvatov, Vadim V; Skulachev, Konstantin V; Dibrova, Daria V; Mulkidjanian, Armen Y

    2017-11-22

    In prokaryotic genomes, functionally coupled genes can be organized in conserved gene clusters enabling their coordinated regulation. Such clusters could contain one or several operons, which are groups of co-transcribed genes. Those genes that evolved from a common ancestral gene by speciation (i.e. orthologs) are expected to have similar genomic neighborhoods in different organisms, whereas those copies of the gene that are responsible for dissimilar functions (i.e. paralogs) could be found in dissimilar genomic contexts. Comparative analysis of genomic neighborhoods facilitates the prediction of co-regulated genes and helps to discern different functions in large protein families. We intended, building on the attribution of gene sequences to the clusters of orthologous groups of proteins (COGs), to provide a method for visualization and comparative analysis of genomic neighborhoods of evolutionary related genes, as well as a respective web server. Here we introduce the COmparative Gene Neighborhoods Analysis Tool (COGNAT), a web server for comparative analysis of genomic neighborhoods. The tool is based on the COG database, as well as the Pfam protein families database. As an example, we show the utility of COGNAT in identifying a new type of membrane protein complex that is formed by paralog(s) of one of the membrane subunits of the NADH:quinone oxidoreductase of type 1 (COG1009) and a cytoplasmic protein of unknown function (COG3002). This article was reviewed by Drs. Igor Zhulin, Uri Gophna and Igor Rogozin.

  13. Genome Scale Modeling in Systems Biology: Algorithms and Resources

    Science.gov (United States)

    Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

    2014-01-01

    In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

  14. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes.

    Science.gov (United States)

    Riechmann, J L; Heard, J; Martin, G; Reuber, L; Jiang, C; Keddie, J; Adam, L; Pineda, O; Ratcliffe, O J; Samaha, R R; Creelman, R; Pilgrim, M; Broun, P; Zhang, J Z; Ghandehari, D; Sherman, B K; Yu, G

    2000-12-15

    The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.

  15. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  16. Diversity of Pseudomonas Genomes, Including Populus-Associated Isolates, as Revealed by Comparative Genome Analysis.

    Science.gov (United States)

    Jun, Se-Ran; Wassenaar, Trudy M; Nookaew, Intawat; Hauser, Loren; Wanchai, Visanu; Land, Miriam; Timm, Collin M; Lu, Tse-Yuan S; Schadt, Christopher W; Doktycz, Mitchel J; Pelletier, Dale A; Ussery, David W

    2016-01-01

    The Pseudomonas genus contains a metabolically versatile group of organisms that are known to occupy numerous ecological niches, including the rhizosphere and endosphere of many plants. Their diversity influences the phylogenetic diversity and heterogeneity of these communities. On the basis of average amino acid identity, comparative genome analysis of >1,000 Pseudomonas genomes, including 21 Pseudomonas strains isolated from the roots of native Populus deltoides (eastern cottonwood) trees resulted in consistent and robust genomic clusters with phylogenetic homogeneity. All Pseudomonas aeruginosa genomes clustered together, and these were clearly distinct from other Pseudomonas species groups on the basis of pangenome and core genome analyses. In contrast, the genomes of Pseudomonas fluorescens were organized into 20 distinct genomic clusters, representing enormous diversity and heterogeneity. Most of our 21 Populus-associated isolates formed three distinct subgroups within the major P. fluorescens group, supported by pathway profile analysis, while two isolates were more closely related to Pseudomonas chlororaphis and Pseudomonas putida. Genes specific to Populus-associated subgroups were identified. Genes specific to subgroup 1 include several sensory systems that act in two-component signal transduction, a TonB-dependent receptor, and a phosphorelay sensor. Genes specific to subgroup 2 contain hypothetical genes, and genes specific to subgroup 3 were annotated with hydrolase activity. This study justifies the need to sequence multiple isolates, especially from P. fluorescens, which displays the most genetic variation, in order to study functional capabilities from a pangenomic perspective. This information will prove useful when choosing Pseudomonas strains for use to promote growth and increase disease resistance in plants. Copyright © 2015 Jun et al.

  17. Analysis tools for the interplay between genome layout and regulation.

    Science.gov (United States)

    Bouyioukos, Costas; Elati, Mohamed; Képès, François

    2016-06-06

    Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

  18. The complete genome sequence and comparative genome analysis of the high pathogenicity Yersinia enterocolitica strain 8081.

    Directory of Open Access Journals (Sweden)

    Nicholas R Thomson

    2006-12-01

    Full Text Available The human enteropathogen, Yersinia enterocolitica, is a significant link in the range of Yersinia pathologies extending from mild gastroenteritis to bubonic plague. Comparison at the genomic level is a key step in our understanding of the genetic basis for this pathogenicity spectrum. Here we report the genome of Y. enterocolitica strain 8081 (serotype 0:8; biotype 1B and extensive microarray data relating to the genetic diversity of the Y. enterocolitica species. Our analysis reveals that the genome of Y. enterocolitica strain 8081 is a patchwork of horizontally acquired genetic loci, including a plasticity zone of 199 kb containing an extraordinarily high density of virulence genes. Microarray analysis has provided insights into species-specific Y. enterocolitica gene functions and the intraspecies differences between the high, low, and nonpathogenic Y. enterocolitica biotypes. Through comparative genome sequence analysis we provide new information on the evolution of the Yersinia. We identify numerous loci that represent ancestral clusters of genes potentially important in enteric survival and pathogenesis, which have been lost or are in the process of being lost, in the other sequenced Yersinia lineages. Our analysis also highlights large metabolic operons in Y. enterocolitica that are absent in the related enteropathogen, Yersinia pseudotuberculosis, indicating major differences in niche and nutrients used within the mammalian gut. These include clusters directing, the production of hydrogenases, tetrathionate respiration, cobalamin synthesis, and propanediol utilisation. Along with ancestral gene clusters, the genome of Y. enterocolitica has revealed species-specific and enteropathogen-specific loci. This has provided important insights into the pathology of this bacterium and, more broadly, into the evolution of the genus. Moreover, wider investigations looking at the patterns of gene loss and gain in the Yersinia have highlighted common

  19. Source Code Analysis Laboratory (SCALe)

    Science.gov (United States)

    2012-04-01

    products (including services) and processes. The agency has also published ISO / IEC 17025 :2005 General Requirements for the Competence of Testing...SCALe undertakes. Testing and calibration laboratories that comply with ISO / IEC 17025 also operate in accordance with ISO 9001. • NIST National...assessed by the accreditation body against all of the requirements of ISO / IEC 17025 : 2005 General requirements for the competence of testing and

  20. A novel statistic for genome-wide interaction analysis.

    Directory of Open Access Journals (Sweden)

    Xuesen Wu

    2010-09-01

    Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

  1. The Methanosarcina barkeri genome: comparative analysis withMethanosarcina acetivorans and Methanosarcina mazei reveals extensiverearrangement within methanosarcinal genomes

    Energy Technology Data Exchange (ETDEWEB)

    Maeder, Dennis L.; Anderson, Iain; Brettin, Thomas S.; Bruce,David C.; Gilna, Paul; Han, Cliff S.; Lapidus, Alla; Metcalf, William W.; Saunders, Elizabeth; Tapia, Roxanne; Sowers, Kevin R.

    2006-05-19

    We report here a comparative analysis of the genome sequence of Methanosarcina barkeri with those of Methanosarcina acetivorans and Methanosarcina mazei. All three genomes share a conserved double origin of replication and many gene clusters. M. barkeri is distinguished by having an organization that is well conserved with respect to the other Methanosarcinae in the region proximal to the origin of replication with interspecies gene similarities as high as 95%. However it is disordered and marked by increased transposase frequency and decreased gene synteny and gene density in the proximal semi-genome. Of the 3680 open reading frames in M. barkeri, 678 had paralogs with better than 80% similarity to both M. acetivorans and M. mazei while 128 nonhypothetical orfs were unique (non-paralogous) amongst these species including a complete formate dehydrogenase operon, two genes required for N-acetylmuramic acid synthesis, a 14 gene gas vesicle cluster and a bacterial P450-specific ferredoxin reductase cluster not previously observed or characterized in this genus. A cryptic 36 kbp plasmid sequence was detected in M. barkeri that contains an orc1 gene flanked by a presumptive origin of replication consisting of 38 tandem repeats of a 143 nt motif. Three-way comparison of these genomes reveals differing mechanisms for the accrual of changes. Elongation of the large M. acetivorans is the result of multiple gene-scale insertions and duplications uniformly distributed in that genome, while M. barkeri is characterized by localized inversions associated with the loss of gene content. In contrast, the relatively short M. mazei most closely approximates the ancestral organizational state.

  2. Comparative analysis of prophages in Streptococcus mutans genomes

    Science.gov (United States)

    Fu, Tiwei; Fan, Xiangyu; Long, Quanxin; Deng, Wanyan; Song, Jinlin

    2017-01-01

    Prophages have been considered genetic units that have an intimate association with novel phenotypic properties of bacterial hosts, such as pathogenicity and genomic variation. Little is known about the genetic information of prophages in the genome of Streptococcus mutans, a major pathogen of human dental caries. In this study, we identified 35 prophage-like elements in S. mutans genomes and performed a comparative genomic analysis. Comparative genomic and phylogenetic analyses of prophage sequences revealed that the prophages could be classified into three main large clusters: Cluster A, Cluster B, and Cluster C. The S. mutans prophages in each cluster were compared. The genomic sequences of phismuN66-1, phismuNLML9-1, and phismu24-1 all shared similarities with the previously reported S. mutans phages M102, M102AD, and ϕAPCM01. The genomes were organized into seven major gene clusters according to the putative functions of the predicted open reading frames: packaging and structural modules, integrase, host lysis modules, DNA replication/recombination modules, transcriptional regulatory modules, other protein modules, and hypothetical protein modules. Moreover, an integrase gene was only identified in phismuNLML9-1 prophages. PMID:29158986

  3. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

    Science.gov (United States)

    Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Cloud computing for genomic data analysis and collaboration.

    Science.gov (United States)

    Langmead, Ben; Nellore, Abhinav

    2018-04-01

    Next-generation sequencing has made major strides in the past decade. Studies based on large sequencing data sets are growing in number, and public archives for raw sequencing data have been doubling in size every 18 months. Leveraging these data requires researchers to use large-scale computational resources. Cloud computing, a model whereby users rent computers and storage from large data centres, is a solution that is gaining traction in genomics research. Here, we describe how cloud computing is used in genomics for research and large-scale collaborations, and argue that its elasticity, reproducibility and privacy features make it ideally suited for the large-scale reanalysis of publicly available archived data, including privacy-protected data.

  5. Genomic Research Data Generation, Analysis and Sharing – Challenges in the African Setting

    Directory of Open Access Journals (Sweden)

    Nicola Mulder

    2017-11-01

    and expensive computing infrastructure which are often unavailable. Recently initiatives such as H3Africa and H3ABioNet which aim to build capacity for large-scale genomics projects in Africa have emerged. Here we describe such initiatives, including the challenges faced in the generation, analysis and sharing of genomic data and how these challenges are being overcome.

  6. Proteomic and genomic analysis of cardiovascular disease

    National Research Council Canada - National Science Library

    Van Eyk, Jennifer; Dunn, M. J

    2003-01-01

    ... to cardiovascular disease. By exploring the various strategies and technical aspects of both, using examples from cardiac or vascular biology, the limitations and the potential of these methods can be clearly seen. The book is divided into three sections: the first focuses on genomics, the second on proteomics, and the third provides an overview of the importance of these two scientific disciplines in drug and diagnostic discovery. The goal of this book is the transfer of their hard-earned lessons to the growing num...

  7. MBGD update 2015: microbial genome database for flexible ortholog analysis utilizing a diverse set of genomic data.

    Science.gov (United States)

    Uchiyama, Ikuo; Mihara, Motohiro; Nishide, Hiroyo; Chiba, Hirokazu

    2015-01-01

    The microbial genome database for comparative analysis (MBGD) (available at http://mbgd.genome.ad.jp/) is a comprehensive ortholog database for flexible comparative analysis of microbial genomes, where the users are allowed to create an ortholog table among any specified set of organisms. Because of the rapid increase in microbial genome data owing to the next-generation sequencing technology, it becomes increasingly challenging to maintain high-quality orthology relationships while allowing the users to incorporate the latest genomic data available into an analysis. Because many of the recently accumulating genomic data are draft genome sequences for which some complete genome sequences of the same or closely related species are available, MBGD now stores draft genome data and allows the users to incorporate them into a user-specific ortholog database using the MyMBGD functionality. In this function, draft genome data are incorporated into an existing ortholog table created only from the complete genome data in an incremental manner to prevent low-quality draft data from affecting clustering results. In addition, to provide high-quality orthology relationships, the standard ortholog table containing all the representative genomes, which is first created by the rapid classification program DomClust, is now refined using DomRefine, a recently developed program for improving domain-level clustering using multiple sequence alignment information. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Genome-Based Comparison of Clostridioides difficile: Average Amino Acid Identity Analysis of Core Genomes.

    Science.gov (United States)

    Cabal, Adriana; Jun, Se-Ran; Jenjaroenpun, Piroon; Wanchai, Visanu; Nookaew, Intawat; Wongsurawat, Thidathip; Burgess, Mary J; Kothari, Atul; Wassenaar, Trudy M; Ussery, David W

    2018-02-14

    Infections due to Clostridioides difficile (previously known as Clostridium difficile) are a major problem in hospitals, where cases can be caused by community-acquired strains as well as by nosocomial spread. Whole genome sequences from clinical samples contain a lot of information but that needs to be analyzed and compared in such a way that the outcome is useful for clinicians or epidemiologists. Here, we compare 663 public available complete genome sequences of C. difficile using average amino acid identity (AAI) scores. This analysis revealed that most of these genomes (640, 96.5%) clearly belong to the same species, while the remaining 23 genomes produce four distinct clusters within the Clostridioides genus. The main C. difficile cluster can be further divided into sub-clusters, depending on the chosen cutoff. We demonstrate that MLST, either based on partial or full gene-length, results in biased estimates of genetic differences and does not capture the true degree of similarity or differences of complete genomes. Presence of genes coding for C. difficile toxins A and B (ToxA/B), as well as the binary C. difficile toxin (CDT), was deduced from their unique PfamA domain architectures. Out of the 663 C. difficile genomes, 535 (80.7%) contained at least one copy of ToxA or ToxB, while these genes were missing from 128 genomes. Although some clusters were enriched for toxin presence, these genes are variably present in a given genetic background. The CDT genes were found in 191 genomes, which were restricted to a few clusters only, and only one cluster lacked the toxin A/B genes consistently. A total of 310 genomes contained ToxA/B without CDT (47%). Further, published metagenomic data from stools were used to assess the presence of C. difficile sequences in blinded cases of C. difficile infection (CDI) and controls, to test if metagenomic analysis is sensitive enough to detect the pathogen, and to establish strain relationships between cases from the same

  9. Comparative genomic analysis by microbial COGs self-attraction rate.

    Science.gov (United States)

    Santoni, Daniele; Romano-Spica, Vincenzo

    2009-06-21

    Whole genome analysis provides new perspectives to determine phylogenetic relationships among microorganisms. The availability of whole nucleotide sequences allows different levels of comparison among genomes by several approaches. In this work, self-attraction rates were considered for each cluster of orthologous groups of proteins (COGs) class in order to analyse gene aggregation levels in physical maps. Phylogenetic relationships among microorganisms were obtained by comparing self-attraction coefficients. Eighteen-dimensional vectors were computed for a set of 168 completely sequenced microbial genomes (19 archea, 149 bacteria). The components of the vector represent the aggregation rate of the genes belonging to each of 18 COGs classes. Genes involved in nonessential functions or related to environmental conditions showed the highest aggregation rates. On the contrary genes involved in basic cellular tasks showed a more uniform distribution along the genome, except for translation genes. Self-attraction clustering approach allowed classification of Proteobacteria, Bacilli and other species belonging to Firmicutes. Rearrangement and Lateral Gene Transfer events may influence divergences from classical taxonomy. Each set of COG classes' aggregation values represents an intrinsic property of the microbial genome. This novel approach provides a new point of view for whole genome analysis and bacterial characterization.

  10. Mycobacterial species as case-study of comparative genome analysis

    DEFF Research Database (Denmark)

    Zakham, F.; Belayachi, L.; Ussery, David

    2011-01-01

    . Pasteur 1173P2, M. leprae Br4923, M. marinum M, M. sp. KMS, M. sp. MCS, M. tuberculosis CDC1551, M. tuberculosis F11, M. tuberculosis H37Ra, M. tuberculosis H37Rv, M. tuberculosis KZN 1435 , M. ulcerans Agy99,and M. vanbaalenii PYR—1, For this purpose a comparison has been done based on their length...... defined for twelve Mycobacterial species. We have also introduced the genome atlas of the reference strain M. tuberculosis H37Rv which can give a good overview of this genome. And for examining the phylogenetic relationships among these bacteria, a phylogenic tree has been constructed from 16S rRNA gene...... the evolutionary events of these species and improving drugs, vaccines, and diagnostics tools for controlling Mycobacterial diseases. In this present study we aim to outline a comparative genome analysis of fourteen Mycobacterial genomes: M. avium subsp. paratuberculosis K—10, M. bovis AF2122/97, M. bovis BCG str...

  11. Genome-wide evolutionary dynamics of influenza B viruses on a global scale.

    Directory of Open Access Journals (Sweden)

    Pinky Langat

    2017-12-01

    Full Text Available The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally.

  12. Genome-wide evolutionary dynamics of influenza B viruses on a global scale

    Science.gov (United States)

    Langat, Pinky; Bowden, Thomas A.; Edwards, Stephanie; Gall, Astrid; Rambaut, Andrew; Daniels, Rodney S.; Russell, Colin A.; Pybus, Oliver G.; McCauley, John

    2017-01-01

    The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally. PMID:29284042

  13. Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Benjamin eMerlet

    2016-02-01

    Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  14. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

    Science.gov (United States)

    Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

    2013-07-01

    In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

  15. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

    Science.gov (United States)

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  16. Genome analysis and comparative genomics of a Giardia intestinalis assemblage E isolate

    Directory of Open Access Journals (Sweden)

    Andersson Jan O

    2010-10-01

    Full Text Available Abstract Background Giardia intestinalis is a protozoan parasite that causes diarrhea in a wide range of mammalian species. To further understand the genetic diversity between the Giardia intestinalis species, we have performed genome sequencing and analysis of a wild-type Giardia intestinalis sample from the assemblage E group, isolated from a pig. Results We identified 5012 protein coding genes, the majority of which are conserved compared to the previously sequenced genomes of the WB and GS strains in terms of microsynteny and sequence identity. Despite this, there is an unexpectedly large number of chromosomal rearrangements and several smaller structural changes that are present in all chromosomes. Novel members of the VSP, NEK Kinase and HCMP gene families were identified, which may reveal possible mechanisms for host specificity and new avenues for antigenic variation. We used comparative genomics of the three diverse Giardia intestinalis isolates P15, GS and WB to define a core proteome for this species complex and to identify lineage-specific genes. Extensive analyses of polymorphisms in the core proteome of Giardia revealed differential rates of divergence among cellular processes. Conclusions Our results indicate that despite a well conserved core of genes there is significant genome variation between Giardia isolates, both in terms of gene content, gene polymorphisms, structural chromosomal variations and surface molecule repertoires. This study improves the annotation of the Giardia genomes and enables the identification of functionally important variation.

  17. Differential DNA Methylation Analysis without a Reference Genome

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    Johanna Klughammer

    2015-12-01

    Full Text Available Genome-wide DNA methylation mapping uncovers epigenetic changes associated with animal development, environmental adaptation, and species evolution. To address the lack of high-throughput methods for DNA methylation analysis in non-model organisms, we developed an integrated approach for studying DNA methylation differences independent of a reference genome. Experimentally, our method relies on an optimized 96-well protocol for reduced representation bisulfite sequencing (RRBS, which we have validated in nine species (human, mouse, rat, cow, dog, chicken, carp, sea bass, and zebrafish. Bioinformatically, we developed the RefFreeDMA software to deduce ad hoc genomes directly from RRBS reads and to pinpoint differentially methylated regions between samples or groups of individuals (http://RefFreeDMA.computational-epigenetics.org. The identified regions are interpreted using motif enrichment analysis and/or cross-mapping to annotated genomes. We validated our method by reference-free analysis of cell-type-specific DNA methylation in the blood of human, cow, and carp. In summary, we present a cost-effective method for epigenome analysis in ecology and evolution, which enables epigenome-wide association studies in natural populations and species without a reference genome.

  18. Revealing less derived nature of cartilaginous fish genomes with their evolutionary time scale inferred with nuclear genes.

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    Adina J Renz

    Full Text Available Cartilaginous fishes, divided into Holocephali (chimaeras and Elasmoblanchii (sharks, rays and skates, occupy a key phylogenetic position among extant vertebrates in reconstructing their evolutionary processes. Their accurate evolutionary time scale is indispensable for better understanding of the relationship between phenotypic and molecular evolution of cartilaginous fishes. However, our current knowledge on the time scale of cartilaginous fish evolution largely relies on estimates using mitochondrial DNA sequences. In this study, making the best use of the still partial, but large-scale sequencing data of cartilaginous fish species, we estimate the divergence times between the major cartilaginous fish lineages employing nuclear genes. By rigorous orthology assessment based on available genomic and transcriptomic sequence resources for cartilaginous fishes, we selected 20 protein-coding genes in the nuclear genome, spanning 2973 amino acid residues. Our analysis based on the Bayesian inference resulted in the mean divergence time of 421 Ma, the late Silurian, for the Holocephali-Elasmobranchii split, and 306 Ma, the late Carboniferous, for the split between sharks and rays/skates. By applying these results and other documented divergence times, we measured the relative evolutionary rate of the Hox A cluster sequences in the cartilaginous fish lineages, which resulted in a lower substitution rate with a factor of at least 2.4 in comparison to tetrapod lineages. The obtained time scale enables mapping phenotypic and molecular changes in a quantitative framework. It is of great interest to corroborate the less derived nature of cartilaginous fish at the molecular level as a genome-wide phenomenon.

  19. Genome scale models of yeast: towards standardized evaluation and consistent omic integration

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Nielsen, Jens

    2015-01-01

    Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

  20. Genome-scale modeling of yeast: chronology, applications and critical perspectives.

    Science.gov (United States)

    Lopes, Helder; Rocha, Isabel

    2017-08-01

    Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.

  1. Bioinformatics analysis of SARS coronavirus genome polymorphism

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    Pavlović-Lažetić Gordana M

    2004-05-01

    Full Text Available Abstract Background We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP, insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs. Results The nucleotide structure of all 38 isolates is presented. Based on insertions and deletions and dissimilarity due to SNPs, the dataset of all the isolates has been qualitatively classified into three groups each having their own subgroups. These are the A-group with "regular" isolates (no insertions / deletions except for 5' and 3' ends, the B-group of isolates with "long insertions", and the C-group of isolates with "many individual" insertions and deletions. The isolate with the smallest average number of SNPs, compared to other isolates, has been identified (TWH. The density distribution of SNPs, insertions and deletions for each group or subgroup, as well as cumulatively for all the isolates is also presented, along with the gene map for TWH. Since individual SNPs may have occurred at random, positions corresponding to multiple SNPs (occurring in two or more isolates are identified and presented. This result revises some previous results of a similar type. Amino acid changes caused by multiple SNPs are also identified (for the annotated sequences, as well as presupposed amino acid changes for non-annotated ones. Exact SNP positions for the isolates in each group or subgroup are presented. Finally, a phylogenetic tree for the SARS-CoV isolates has been produced using the CLUSTALW program, showing high compatibility with former qualitative classification. Conclusions The comparative study of SARS-CoV isolates provides essential information for genome

  2. Genome-wide Analysis of Gene Regulation

    DEFF Research Database (Denmark)

    Chen, Yun

    to protein: through epigenetic modifications, transcription regulators or post-transcriptional controls. The following papers concern several layers of gene regulation with questions answered by different HTS approaches. Genome-wide screening of epigenetic changes by ChIP-seq allowed us to study both spatial...... and temporal alterations of histone modifications (Papers I and II). Coupling the data with machine learning approaches, we established a prediction framework to assess the most informative histone marks as well as their most influential nucleosome positions in predicting the promoter usages. (Papers I...... they regulated or if the sites had global elevated usage rates by multiple TFs. Using RNA-seq, 5’end-seq in combination with depletion of 5’exonuclease as well as nonsensemediated decay (NMD) factors, we systematically analyzed NMD substrates as well as their degradation intermediates in human cells (Paper V...

  3. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

  4. Enumeration of smallest intervention strategies in genome-scale metabolic networks.

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    Axel von Kamp

    2014-01-01

    Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

  5. Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Jolly Emmitt R

    2005-11-01

    Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.

  6. Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

    Science.gov (United States)

    Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2017-02-01

    Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

  7. Detection and analysis of ancient segmental duplications in mammalian genomes.

    Science.gov (United States)

    Pu, Lianrong; Lin, Yu; Pevzner, Pavel A

    2018-05-07

    Although segmental duplications (SDs) represent hotbeds for genomic rearrangements and emergence of new genes, there are still no easy-to-use tools for identifying SDs. Moreover, while most previous studies focused on recently emerged SDs, detection of ancient SDs remains an open problem. We developed an SDquest algorithm for SD finding and applied it to analyzing SDs in human, gorilla, and mouse genomes. Our results demonstrate that previous studies missed many SDs in these genomes and show that SDs account for at least 6.05% of the human genome (version hg19), a 17% increase as compared to the previous estimate. Moreover, SDquest classified 6.42% of the latest GRCh38 version of the human genome as SDs, a large increase as compared to previous studies. We thus propose to re-evaluate evolution of SDs based on their accurate representation across multiple genomes. Toward this goal, we analyzed the complex mosaic structure of SDs and decomposed mosaic SDs into elementary SDs, a prerequisite for follow-up evolutionary analysis. We also introduced the concept of the breakpoint graph of mosaic SDs that revealed SD hotspots and suggested that some SDs may have originated from circular extrachromosomal DNA (ecDNA), not unlike ecDNA that contributes to accelerated evolution in cancer. © 2018 Pu et al.; Published by Cold Spring Harbor Laboratory Press.

  8. Comparative genomics of Mycoplasma: analysis of conserved essential genes and diversity of the pan-genome.

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    Wei Liu

    Full Text Available Mycoplasma, the smallest self-replicating organism with a minimal metabolism and little genomic redundancy, is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. This study employs comparative evolutionary analysis of twenty Mycoplasma genomes to gain an improved understanding of essential genes. By analyzing the core genome of mycoplasmas, we finally revealed the conserved essential genes set for mycoplasma survival. Further analysis showed that the core genome set has many characteristics in common with experimentally identified essential genes. Several key genes, which are related to DNA replication and repair and can be disrupted in transposon mutagenesis studies, may be critical for bacteria survival especially over long period natural selection. Phylogenomic reconstructions based on 3,355 homologous groups allowed robust estimation of phylogenetic relatedness among mycoplasma strains. To obtain deeper insight into the relative roles of molecular evolution in pathogen adaptation to their hosts, we also analyzed the positive selection pressures on particular sites and lineages. There appears to be an approximate correlation between the divergence of species and the level of positive selection detected in corresponding lineages.

  9. A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

    Science.gov (United States)

    Luo, Li; Zhu, Yun; Xiong, Momiao

    2012-06-01

    The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

  10. Quantitative high-resolution genomic analysis of single cancer cells.

    Science.gov (United States)

    Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

    2011-01-01

    During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

  11. Quantitative high-resolution genomic analysis of single cancer cells.

    Directory of Open Access Journals (Sweden)

    Juliane Hannemann

    Full Text Available During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

  12. Genomic analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea.

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    Joelle Amselem

    2011-08-01

    Full Text Available Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38-39 Mb genomes include 11,860-14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared to <1% of B. cinerea. The arsenal of genes associated with necrotrophic processes is similar between the species, including genes involved in plant cell wall degradation and oxalic acid production. Analysis of secondary metabolism gene clusters revealed an expansion in number and diversity of B. cinerea-specific secondary metabolites relative to S. sclerotiorum. The potential diversity in secondary metabolism might be involved in adaptation to specific ecological niches. Comparative genome analysis revealed the basis of differing sexual mating compatibility systems between S. sclerotiorum and B. cinerea. The organization of the mating-type loci differs, and their structures provide evidence for the evolution of heterothallism from homothallism. These data shed light on the evolutionary and mechanistic bases of the genetically complex traits of necrotrophic pathogenicity and sexual mating. This resource should facilitate the functional studies designed to better understand what makes these

  13. Genome-wide Studies of Mycolic Acid Bacteria: Computational Identification and Analysis of a Minimal Genome

    KAUST Repository

    Kamanu, Frederick Kinyua

    2012-12-01

    The mycolic acid bacteria are a distinct suprageneric group of asporogenous Grampositive, high GC-content bacteria, distinguished by the presence of mycolic acids in their cell envelope. They exhibit great diversity in their cell and morphology; although primarily non-pathogens, this group contains three major pathogens Mycobacterium leprae, Mycobacterium tuberculosis complex, and Corynebacterium diphtheria. Although the mycolic acid bacteria are a clearly defined group of bacteria, the taxonomic relationships between its constituent genera and species are less well defined. Two approaches were tested for their suitability in describing the taxonomy of the group. First, a Multilocus Sequence Typing (MLST) experiment was assessed and found to be superior to monophyletic (16S small ribosomal subunit) in delineating a total of 52 mycolic acid bacterial species. Phylogenetic inference was performed using the neighbor-joining method. To further refine phylogenetic analysis and to take advantage of the widespread availability of bacterial genome data, a computational framework that simulates DNA-DNA hybridisation was developed and validated using multiscale bootstrap resampling. The tool classifies microbial genomes based on whole genome DNA, and was deployed as a web-application using PHP and Javascript. It is accessible online at http://cbrc.kaust.edu.sa/dna_hybridization/ A third study was a computational and statistical methods in the identification and analysis of a putative minimal mycolic acid bacterial genome so as to better understand (1) the genomic requirements to encode a mycolic acid bacterial cell and (2) the role and type of genes and genetic elements that lead to the massive increase in genome size in environmental mycolic acid bacteria. Using a reciprocal comparison approach, a total of 690 orthologous gene clusters forming a putative minimal genome were identified across 24 mycolic acid bacterial species. In order to identify new potential drug

  14. Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study.

    Directory of Open Access Journals (Sweden)

    Paul S de Vries

    Full Text Available An increasing number of genome-wide association (GWA studies are now using the higher resolution 1000 Genomes Project reference panel (1000G for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8, the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

  15. Large Scale Sequencing of Dothideomycetes Provides Insights into Genome Evolution and Adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Haridas, Sajeet; Crous, Pedro; Binder, Manfred; Spatafora, Joseph; Grigoriev, Igor

    2015-03-16

    Dothideomycetes is the largest and most diverse class of ascomycete fungi with 23 orders 110 families, 1300 genera and over 19,000 known species. We present comparative analysis of 70 Dothideomycete genomes including over 50 that we sequenced and are as yet unpublished. This extensive sampling has almost quadrupled the previous study of 18 species and uncovered a 10 fold range of genome sizes. We were able to clarify the phylogenetic positions of several species whose origins were unclear in previous morphological and sequence comparison studies. We analyzed selected gene families including proteases, transporters and small secreted proteins and show that major differences in gene content is influenced by speciation.

  16. Functional genomic analysis of C. elegans molting.

    Directory of Open Access Journals (Sweden)

    Alison R Frand

    2005-10-01

    Full Text Available Although the molting cycle is a hallmark of insects and nematodes, neither the endocrine control of molting via size, stage, and nutritional inputs nor the enzymatic mechanism for synthesis and release of the exoskeleton is well understood. Here, we identify endocrine and enzymatic regulators of molting in C. elegans through a genome-wide RNA-interference screen. Products of the 159 genes discovered include annotated transcription factors, secreted peptides, transmembrane proteins, and extracellular matrix enzymes essential for molting. Fusions between several genes and green fluorescent protein show a pulse of expression before each molt in epithelial cells that synthesize the exoskeleton, indicating that the corresponding proteins are made in the correct time and place to regulate molting. We show further that inactivation of particular genes abrogates expression of the green fluorescent protein reporter genes, revealing regulatory networks that might couple the expression of genes essential for molting to endocrine cues. Many molting genes are conserved in parasitic nematodes responsible for human disease, and thus represent attractive targets for pesticide and pharmaceutical development.

  17. Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data.

    Science.gov (United States)

    Duforet-Frebourg, Nicolas; Luu, Keurcien; Laval, Guillaume; Bazin, Eric; Blum, Michael G B

    2016-04-01

    To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  18. The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

    Science.gov (United States)

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

  19. Scaling analysis of meteorite shower mass distributions

    DEFF Research Database (Denmark)

    Oddershede, Lene; Meibom, A.; Bohr, Jakob

    1998-01-01

    Meteorite showers are the remains of extraterrestrial objects which are captivated by the gravitational field of the Earth. We have analyzed the mass distribution of fragments from 16 meteorite showers for scaling. The distributions exhibit distinct scaling behavior over several orders of magnetude......; the observed scaling exponents vary from shower to shower. Half of the analyzed showers show a single scaling region while the orther half show multiple scaling regimes. Such an analysis can provide knowledge about the fragmentation process and about the original meteoroid. We also suggest to compare...... the observed scaling exponents to exponents observed in laboratory experiments and discuss the possibility that one can derive insight into the original shapes of the meteoroids....

  20. A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Héloïse Bastide

    2013-06-01

    Full Text Available Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

  1. A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

    Science.gov (United States)

    Bastide, Héloïse; Betancourt, Andrea; Nolte, Viola; Tobler, Raymond; Stöbe, Petra; Futschik, Andreas; Schlötterer, Christian

    2013-06-01

    Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS) to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs) segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

  2. Genome-wide identification, functional analysis and expression ...

    African Journals Online (AJOL)

    The plant pleiotropic drug resistance (PDR) family of ATP-binding cassette (ABC) transporters has comprehensively been researched in relation to transport of antifungal agents and resistant pathogens. In our study, analyses of the whole family of PDR genes present in the potato genome were provided. This analysis ...

  3. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  4. Genome Assembly and Computational Analysis Pipelines for Bacterial Pathogens

    KAUST Repository

    Rangkuti, Farania Gama Ardhina

    2011-06-01

    Pathogens lie behind the deadliest pandemics in history. To date, AIDS pandemic has resulted in more than 25 million fatal cases, while tuberculosis and malaria annually claim more than 2 million lives. Comparative genomic analyses are needed to gain insights into the molecular mechanisms of pathogens, but the abundance of biological data dictates that such studies cannot be performed without the assistance of computational approaches. This explains the significant need for computational pipelines for genome assembly and analyses. The aim of this research is to develop such pipelines. This work utilizes various bioinformatics approaches to analyze the high-­throughput genomic sequence data that has been obtained from several strains of bacterial pathogens. A pipeline has been compiled for quality control for sequencing and assembly, and several protocols have been developed to detect contaminations. Visualization has been generated of genomic data in various formats, in addition to alignment, homology detection and sequence variant detection. We have also implemented a metaheuristic algorithm that significantly improves bacterial genome assemblies compared to other known methods. Experiments on Mycobacterium tuberculosis H37Rv data showed that our method resulted in improvement of N50 value of up to 9697% while consistently maintaining high accuracy, covering around 98% of the published reference genome. Other improvement efforts were also implemented, consisting of iterative local assemblies and iterative correction of contiguated bases. Our result expedites the genomic analysis of virulent genes up to single base pair resolution. It is also applicable to virtually every pathogenic microorganism, propelling further research in the control of and protection from pathogen-­associated diseases.

  5. Sequencing and Analysis of Neanderthal Genomic DNA

    Energy Technology Data Exchange (ETDEWEB)

    Noonan, James P.; Coop, Graham; Kudaravalli, Sridhar; Smith,Doug; Krause, Johannes; Alessi, Joe; Chen, Feng; Platt, Darren; Paabo,Svante; Pritchard, Jonathan K.; Rubin, Edward M.

    2006-06-13

    Recovery and analysis of multiple Neanderthal autosomalsequences using a metagenomic approach reveals that modern humans andNeanderthals split ~;400,000 years ago, without significant evidence ofsubsequent admixture.

  6. Phylogeny and comparative genome analysis of a Basidiomycete fungi

    Energy Technology Data Exchange (ETDEWEB)

    Riley, Robert W.; Salamov, Asaf; Grigoriev, Igor; Hibbett, David

    2011-03-14

    Fungi of the phylum Basidiomycota, make up some 37percent of the described fungi, and are important from the perspectives of forestry, agriculture, medicine, and bioenergy. This diverse phylum includes the mushrooms, wood rots, plant pathogenic rusts and smuts, and some human pathogens. To better understand these important fungi, we have undertaken a comparative genomic analysis of the Basidiomycetes with available sequenced genomes. We report a phylogeny that sheds light on previously unclear evolutionary relationships among the Basidiomycetes. We also define a `core proteome? based on protein families conserved in all Basidiomycetes. We identify key expansions and contractions in protein families that may be responsible for the degradation of plant biomass such as cellulose, hemicellulose, and lignin. Finally, we speculate as to the genomic changes that drove such expansions and contractions.

  7. Sequence analysis of the genome of carnation (Dianthus caryophyllus L.).

    Science.gov (United States)

    Yagi, Masafumi; Kosugi, Shunichi; Hirakawa, Hideki; Ohmiya, Akemi; Tanase, Koji; Harada, Taro; Kishimoto, Kyutaro; Nakayama, Masayoshi; Ichimura, Kazuo; Onozaki, Takashi; Yamaguchi, Hiroyasu; Sasaki, Nobuhiro; Miyahara, Taira; Nishizaki, Yuzo; Ozeki, Yoshihiro; Nakamura, Noriko; Suzuki, Takamasa; Tanaka, Yoshikazu; Sato, Shusei; Shirasawa, Kenta; Isobe, Sachiko; Miyamura, Yoshinori; Watanabe, Akiko; Nakayama, Shinobu; Kishida, Yoshie; Kohara, Mitsuyo; Tabata, Satoshi

    2014-06-01

    The whole-genome sequence of carnation (Dianthus caryophyllus L.) cv. 'Francesco' was determined using a combination of different new-generation multiplex sequencing platforms. The total length of the non-redundant sequences was 568,887,315 bp, consisting of 45,088 scaffolds, which covered 91% of the 622 Mb carnation genome estimated by k-mer analysis. The N50 values of contigs and scaffolds were 16,644 bp and 60,737 bp, respectively, and the longest scaffold was 1,287,144 bp. The average GC content of the contig sequences was 36%. A total of 1050, 13, 92 and 143 genes for tRNAs, rRNAs, snoRNA and miRNA, respectively, were identified in the assembled genomic sequences. For protein-encoding genes, 43 266 complete and partial gene structures excluding those in transposable elements were deduced. Gene coverage was ∼ 98%, as deduced from the coverage of the core eukaryotic genes. Intensive characterization of the assigned carnation genes and comparison with those of other plant species revealed characteristic features of the carnation genome. The results of this study will serve as a valuable resource for fundamental and applied research of carnation, especially for breeding new carnation varieties. Further information on the genomic sequences is available at http://carnation.kazusa.or.jp. © The Author 2013. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  8. The Chlamydia psittaci genome: a comparative analysis of intracellular pathogens.

    Science.gov (United States)

    Voigt, Anja; Schöfl, Gerhard; Saluz, Hans Peter

    2012-01-01

    Chlamydiaceae are a family of obligate intracellular pathogens causing a wide range of diseases in animals and humans, and facing unique evolutionary constraints not encountered by free-living prokaryotes. To investigate genomic aspects of infection, virulence and host preference we have sequenced Chlamydia psittaci, the pathogenic agent of ornithosis. A comparison of the genome of the avian Chlamydia psittaci isolate 6BC with the genomes of other chlamydial species, C. trachomatis, C. muridarum, C. pneumoniae, C. abortus, C. felis and C. caviae, revealed a high level of sequence conservation and synteny across taxa, with the major exception of the human pathogen C. trachomatis. Important differences manifest in the polymorphic membrane protein family specific for the Chlamydiae and in the highly variable chlamydial plasticity zone. We identified a number of psittaci-specific polymorphic membrane proteins of the G family that may be related to differences in host-range and/or virulence as compared to closely related Chlamydiaceae. We calculated non-synonymous to synonymous substitution rate ratios for pairs of orthologous genes to identify putative targets of adaptive evolution and predicted type III secreted effector proteins. This study is the first detailed analysis of the Chlamydia psittaci genome sequence. It provides insights in the genome architecture of C. psittaci and proposes a number of novel candidate genes mostly of yet unknown function that may be important for pathogen-host interactions.

  9. The Chlamydia psittaci genome: a comparative analysis of intracellular pathogens.

    Directory of Open Access Journals (Sweden)

    Anja Voigt

    Full Text Available Chlamydiaceae are a family of obligate intracellular pathogens causing a wide range of diseases in animals and humans, and facing unique evolutionary constraints not encountered by free-living prokaryotes. To investigate genomic aspects of infection, virulence and host preference we have sequenced Chlamydia psittaci, the pathogenic agent of ornithosis.A comparison of the genome of the avian Chlamydia psittaci isolate 6BC with the genomes of other chlamydial species, C. trachomatis, C. muridarum, C. pneumoniae, C. abortus, C. felis and C. caviae, revealed a high level of sequence conservation and synteny across taxa, with the major exception of the human pathogen C. trachomatis. Important differences manifest in the polymorphic membrane protein family specific for the Chlamydiae and in the highly variable chlamydial plasticity zone. We identified a number of psittaci-specific polymorphic membrane proteins of the G family that may be related to differences in host-range and/or virulence as compared to closely related Chlamydiaceae. We calculated non-synonymous to synonymous substitution rate ratios for pairs of orthologous genes to identify putative targets of adaptive evolution and predicted type III secreted effector proteins.This study is the first detailed analysis of the Chlamydia psittaci genome sequence. It provides insights in the genome architecture of C. psittaci and proposes a number of novel candidate genes mostly of yet unknown function that may be important for pathogen-host interactions.

  10. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

  11. Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

    Science.gov (United States)

    Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

    2012-01-01

    Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

  12. Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

    Directory of Open Access Journals (Sweden)

    Yuichi Shiraishi

    Full Text Available Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV-related hepatocellular carcinomas (HCCs and their matched controls. Comparison of whole genome sequence (WGS and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3, and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.

  13. Genome-scale prediction of proteins with long intrinsically disordered regions.

    Science.gov (United States)

    Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

    2014-01-01

    Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

  14. H2@Scale Resource and Market Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, Mark

    2017-05-04

    The 'H2@Scale' concept is based on the potential for wide-scale utilization of hydrogen as an energy intermediate where the hydrogen is produced from low cost energy resources and it is used in both the transportation and industrial sectors. H2@Scale has the potential to address grid resiliency, energy security, and cross-sectoral emissions reductions. This presentation summarizes the status of an ongoing analysis effort to quantify the benefits of H2@Scale. It includes initial results regarding market potential, resource potential, and impacts of when electrolytic hydrogen is produced with renewable electricity to meet the potential market demands. It also proposes additional analysis efforts to better quantify each of the factors.

  15. Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications.

    Science.gov (United States)

    Christen, Matthias; Del Medico, Luca; Christen, Heinz; Christen, Beat

    2017-01-01

    Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner.

  16. Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications.

    Directory of Open Access Journals (Sweden)

    Matthias Christen

    Full Text Available Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner.

  17. Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus and the Scaled Quail (Callipepla squamata Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size

    Directory of Open Access Journals (Sweden)

    David L. Oldeschulte

    2017-09-01

    Full Text Available Northern bobwhite (Colinus virginianus; hereafter bobwhite and scaled quail (Callipepla squamata populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0 and second- (v2.0 generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb, which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%, genome-wide repetitive content (10.40%; 10.43%, and MAKER-predicted protein coding genes (17,131; 17,165 were similar for the scaled quail (v1.0 and bobwhite (v2.0 assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8% and the bobwhite (v2.0; 82.5%, as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0, and 711 in the bobwhite genome (v2.0, including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0 and bobwhite (v2.0 genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15–20 KYA.

  18. Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus) and the Scaled Quail (Callipepla squamata) Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size.

    Science.gov (United States)

    Oldeschulte, David L; Halley, Yvette A; Wilson, Miranda L; Bhattarai, Eric K; Brashear, Wesley; Hill, Joshua; Metz, Richard P; Johnson, Charles D; Rollins, Dale; Peterson, Markus J; Bickhart, Derek M; Decker, Jared E; Sewell, John F; Seabury, Christopher M

    2017-09-07

    Northern bobwhite ( Colinus virginianus ; hereafter bobwhite) and scaled quail ( Callipepla squamata ) populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0) and second- (v2.0) generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb) was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb), which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%), genome-wide repetitive content (10.40%; 10.43%), and MAKER-predicted protein coding genes (17,131; 17,165) were similar for the scaled quail (v1.0) and bobwhite (v2.0) assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8%) and the bobwhite (v2.0; 82.5%), as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0), and 711 in the bobwhite genome (v2.0), including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0) and bobwhite (v2.0) genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15-20 KYA. Copyright © 2017 Oldeschulte et al.

  19. Viral genome analysis and knowledge management.

    Science.gov (United States)

    Kuiken, Carla; Yoon, Hyejin; Abfalterer, Werner; Gaschen, Brian; Lo, Chienchi; Korber, Bette

    2013-01-01

    One of the challenges of genetic data analysis is to combine information from sources that are distributed around the world and accessible through a wide array of different methods and interfaces. The HIV database and its footsteps, the hepatitis C virus (HCV) and hemorrhagic fever virus (HFV) databases, have made it their mission to make different data types easily available to their users. This involves a large amount of behind-the-scenes processing, including quality control and analysis of the sequences and their annotation. Gene and protein sequences are distilled from the sequences that are stored in GenBank; to this end, both submitter annotation and script-generated sequences are used. Alignments of both nucleotide and amino acid sequences are generated, manually curated, distilled into an alignment model, and regenerated in an iterative cycle that results in ever better new alignments. Annotation of epidemiological and clinical information is parsed, checked, and added to the database. User interfaces are updated, and new interfaces are added based upon user requests. Vital for its success, the database staff are heavy users of the system, which enables them to fix bugs and find opportunities for improvement. In this chapter we describe some of the infrastructure that keeps these heavily used analysis platforms alive and vital after nearly 25 years of use. The database/analysis platforms described in this chapter can be accessed at http://hiv.lanl.gov http://hcv.lanl.gov http://hfv.lanl.gov.

  20. New genomic resources for switchgrass: a BAC library and comparative analysis of homoeologous genomic regions harboring bioenergy traits

    Directory of Open Access Journals (Sweden)

    Feltus Frank A

    2011-07-01

    Full Text Available Abstract Background Switchgrass, a C4 species and a warm-season grass native to the prairies of North America, has been targeted for development into an herbaceous biomass fuel crop. Genetic improvement of switchgrass feedstock traits through marker-assisted breeding and biotechnology approaches calls for genomic tools development. Establishment of integrated physical and genetic maps for switchgrass will accelerate mapping of value added traits useful to breeding programs and to isolate important target genes using map based cloning. The reported polyploidy series in switchgrass ranges from diploid (2X = 18 to duodecaploid (12X = 108. Like in other large, repeat-rich plant genomes, this genomic complexity will hinder whole genome sequencing efforts. An extensive physical map providing enough information to resolve the homoeologous genomes would provide the necessary framework for accurate assembly of the switchgrass genome. Results A switchgrass BAC library constructed by partial digestion of nuclear DNA with EcoRI contains 147,456 clones covering the effective genome approximately 10 times based on a genome size of 3.2 Gigabases (~1.6 Gb effective. Restriction digestion and PFGE analysis of 234 randomly chosen BACs indicated that 95% of the clones contained inserts, ranging from 60 to 180 kb with an average of 120 kb. Comparative sequence analysis of two homoeologous genomic regions harboring orthologs of the rice OsBRI1 locus, a low-copy gene encoding a putative protein kinase and associated with biomass, revealed that orthologous clones from homoeologous chromosomes can be unambiguously distinguished from each other and correctly assembled to respective fingerprint contigs. Thus, the data obtained not only provide genomic resources for further analysis of switchgrass genome, but also improve efforts for an accurate genome sequencing strategy. Conclusions The construction of the first switchgrass BAC library and comparative analysis of

  1. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Directory of Open Access Journals (Sweden)

    Katsunori Yoshikawa

    Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  2. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-03-27

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

  3. Genome-Wide Detection and Analysis of Multifunctional Genes

    Science.gov (United States)

    Pritykin, Yuri; Ghersi, Dario; Singh, Mona

    2015-01-01

    Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

  4. Genomic analysis and selected molecular pathways in rare cancers

    International Nuclear Information System (INIS)

    Liu, Stephen V; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Demeure, Michael J; Ramanathan, Ramesh K; Von Hoff, Daniel D; Barrett, Michael T; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Eng, Cathy

    2012-01-01

    It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer. (paper)

  5. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

    Directory of Open Access Journals (Sweden)

    Laura Navone

    2018-06-01

    Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  6. Analysis of radiation-induced genome alterations in Vigna unguiculata

    Directory of Open Access Journals (Sweden)

    van der Vyver C

    2011-09-01

    Full Text Available Christell van der Vyver1, B Juan Vorster2, Karl J Kunert3, Christopher A Cullis41Institute for Plant Biotechnology, Department of Genetics, University of Stellenbosch, Stellenbosch, South Africa; 2Department of Plant Production and Soil Science, and 3Department of Plant Science, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, South Africa; 4Case Western Reserve University, Department of Biology, Cleveland, OH, USAAbstract: Seeds from an inbred Vigna unguiculata (cowpea cultivar were gamma-irradiated with a dose of 180 Gy in order to identify and characterize possible mutations. Three techniques, ie, random amplified polymorphic DNA, microsatellites, and representational difference analysis, were used to characterize possible DNA variation among the mutants and nonirradiated control plants both immediately after irradiation and in subsequent generations. A large portion of putative radiation-induced genome changes had significant similarities to chloroplast sequences. The frequency of mutation at three of these isolated polymorphic regions with chloroplast similarity was further determined by polymerase chain reaction screening using a large number of individual parental, M1, and M2 plants. Analysis of these sequences indicated that the rate at which various regions of the genome is mutated in irradiation experiments differs significantly and also that mutations have variable “repair” rates. Furthermore, regions of the nuclear DNA derived from the chloroplast genome are highly susceptible to modification by radiation treatment. Overall, data have provided detailed information on the effects of gamma irradiation on the cowpea genome and about the ability of the plant to repair these genome changes in subsequent plant generations.Keywords: mutation breeding, gamma radiation, genetic mutations, cowpea, representational difference analysis

  7. Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

    Science.gov (United States)

    Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

    2017-11-01

    The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  8. Genome-scale modeling of the protein secretory machinery in yeast

    DEFF Research Database (Denmark)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina

    2013-01-01

    The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

  9. Corroded scale analysis from water distribution pipes

    Directory of Open Access Journals (Sweden)

    Rajaković-Ognjanović Vladana N.

    2011-01-01

    Full Text Available The subject of this study was the steel pipes that are part of Belgrade's drinking water supply network. In order to investigate the mutual effects of corrosion and water quality, the corrosion scales on the pipes were analyzed. The idea was to improve control of corrosion processes and prevent impact of corrosion on water quality degradation. The instrumental methods for corrosion scales characterization used were: scanning electron microscopy (SEM, for the investigation of corrosion scales of the analyzed samples surfaces, X-ray diffraction (XRD, for the analysis of the presence of solid forms inside scales, scanning electron microscopy (SEM, for the microstructural analysis of the corroded scales, and BET adsorption isotherm for the surface area determination. Depending on the composition of water next to the pipe surface, corrosion of iron results in the formation of different compounds and solid phases. The composition and structure of the iron scales in the drinking water distribution pipes depends on the type of the metal and the composition of the aqueous phase. Their formation is probably governed by several factors that include water quality parameters such as pH, alkalinity, buffer intensity, natural organic matter (NOM concentration, and dissolved oxygen (DO concentration. Factors such as water flow patterns, seasonal fluctuations in temperature, and microbiological activity as well as water treatment practices such as application of corrosion inhibitors can also influence corrosion scale formation and growth. Therefore, the corrosion scales found in iron and steel pipes are expected to have unique features for each site. Compounds that are found in iron corrosion scales often include goethite, lepidocrocite, magnetite, hematite, ferrous oxide, siderite, ferrous hydroxide, ferric hydroxide, ferrihydrite, calcium carbonate and green rusts. Iron scales have characteristic features that include: corroded floor, porous core that contains

  10. Large-Scale Analysis of Art Proportions

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2014-01-01

    While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square) and with majo......While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square...

  11. Integrative Genomic Analysis of Complex traits

    DEFF Research Database (Denmark)

    Ehsani, Ali Reza

    In the last decade rapid development in biotechnologies has made it possible to extract extensive information about practically all levels of biological organization. An ever-increasing number of studies are reporting miltilayered datasets on the entire DNA sequence, transceroption, protein...... expression, and metabolite abundance of more and more populations in a multitude of invironments. However, a solid model for including all of this complex information in one analysis, to disentangle genetic variation and the underlying genetic architecture of complex traits and diseases, has not yet been...

  12. Genomes

    National Research Council Canada - National Science Library

    Brown, T. A. (Terence A.)

    2002-01-01

    ... of genome expression and replication processes, and transcriptomics and proteomics. This text is richly illustrated with clear, easy-to-follow, full color diagrams, which are downloadable from the book's website...

  13. Atlas2 Cloud: a framework for personal genome analysis in the cloud.

    Science.gov (United States)

    Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli

    2012-01-01

    Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

  14. Segregation distortion causes large-scale differences between male and female genomes in hybrid ants.

    Science.gov (United States)

    Kulmuni, Jonna; Seifert, Bernhard; Pamilo, Pekka

    2010-04-20

    Hybridization in isolated populations can lead either to hybrid breakdown and extinction or in some cases to speciation. The basis of hybrid breakdown lies in genetic incompatibilities between diverged genomes. In social Hymenoptera, the consequences of hybridization can differ from those in other animals because of haplodiploidy and sociality. Selection pressures differ between sexes because males are haploid and females are diploid. Furthermore, sociality and group living may allow survival of hybrid genotypes. We show that hybridization in Formica ants has resulted in a stable situation in which the males form two highly divergent gene pools whereas all the females are hybrids. This causes an exceptional situation with large-scale differences between male and female genomes. The genotype differences indicate strong transmission ratio distortion depending on offspring sex, whereby the mother transmits some alleles exclusively to her daughters and other alleles exclusively to her sons. The genetic differences between the sexes and the apparent lack of multilocus hybrid genotypes in males can be explained by recessive incompatibilities which cause the elimination of hybrid males because of their haploid genome. Alternatively, differentiation between sexes could be created by prezygotic segregation into male-forming and female-forming gametes in diploid females. Differentiation between sexes is stable and maintained throughout generations. The present study shows a unique outcome of hybridization and demonstrates that hybridization has the potential of generating evolutionary novelties in animals.

  15. Comparative Genome Analysis of Basidiomycete Fungi

    Energy Technology Data Exchange (ETDEWEB)

    Riley, Robert; Salamov, Asaf; Morin, Emmanuelle; Nagy, Laszlo; Manning, Gerard; Baker, Scott; Brown, Daren; Henrissat, Bernard; Levasseur, Anthony; Hibbett, David; Martin, Francis; Grigoriev, Igor

    2012-03-19

    Fungi of the phylum Basidiomycota (basidiomycetes), make up some 37percent of the described fungi, and are important in forestry, agriculture, medicine, and bioenergy. This diverse phylum includes the mushrooms, wood rots, symbionts, and plant and animal pathogens. To better understand the diversity of phenotypes in basidiomycetes, we performed a comparative analysis of 35 basidiomycete fungi spanning the diversity of the phylum. Phylogenetic patterns of lignocellulose degrading genes suggest a continuum rather than a sharp dichotomy between the white rot and brown rot modes of wood decay. Patterns of secondary metabolic enzymes give additional insight into the broad array of phenotypes found in the basidiomycetes. We suggest that the profile of an organism in lignocellulose-targeting genes can be used to predict its nutritional mode, and predict Dacryopinax sp. as a brown rot; Botryobasidium botryosum and Jaapia argillacea as white rots.

  16. Genome-wide analysis of tandem repeats in plants and green algae

    Science.gov (United States)

    Zhixin Zhao; Cheng Guo; Sreeskandarajan Sutharzan; Pei Li; Craig Echt; Jie Zhang; Chun Liang

    2014-01-01

    Tandem repeats (TRs) extensively exist in the genomes of prokaryotes and eukaryotes. Based on the sequenced genomes and gene annotations of 31 plant and algal species in Phytozome version 8.0 (http://www.phytozome.net/), we examined TRs in a genome-wide scale, characterized their distributions and motif features, and explored their putative biological functions. Among...

  17. Sexagesimal scale for mapping human genome Escala sexagesimal para mapear el genoma humano

    Directory of Open Access Journals (Sweden)

    RICARDO CRUZ-COKE

    2001-03-01

    Full Text Available In a previous work I designed a diagram of the human genome based on a circular ideogram of the haploid set of chromosomes, using a low resolution scale of Megabase units. The purpose of this work is to draft a new scale to measure the physical map of the human genome at the highest resolution level. The entire length of the haploid genome of males is deployed in a circumference, marked with a sexagesimal scale with 360 degrees and 1296000 arc seconds. The radio of this circunference displays a semilogaritmic metric scale from 1 m up to the nanometer level. The base pair level of DNA sequences, 10-9 of this circunsference, is measured in milliarsec unit (mas, equivalent to a thousand of arcsecond. The "mas" unit, correspond to 1.27 nanometers (nm or 0.427 base pair (bp and it is the framework for measure DNA sequences. Thus the three billion base pairs of the human genome may be identified by 1296000000 "mas" units in continous correlation from number 1 to number 1296000000. This sexagesimal scale covers all the levels of the nuclear genetic material, from nucleotides to chromosomes. The locations of every codon and every gene may be numbered in the physical map of chomosome regions according to this new scale, instead of the partial kilobase and Megabase scales used today. The advantage of the new scale is the unification of the set of chromosomes under a continous scale of measurement at the DNA level, facilitating the correlation with the phenotypes of man and other speciesEn un trabajo anterior yo diseñé un diagrama del genoma humano basado en un ideograma circular del conjunto haploide de cromosomas, usando una escala de baja resolución en megabases. El propósito de este trabajo es el de diseñar una nueva escala para medir el mapa físico del genoma humano al más alto nivel de resolución. La longitud completa del genoma haploide del varon es extendido en una circunsferencia, marcada con una escala sexagesimal de 360 grados y 1296000

  18. Comparative genomic analysis of multidrug-resistant Streptococcus pneumoniae isolates

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    Pan F

    2018-05-01

    Full Text Available Fen Pan,1 Hong Zhang,1 Xiaoyan Dong,2 Weixing Ye,3 Ping He,4 Shulin Zhang,4 Jeff Xianchao Zhu,5 Nanbert Zhong1,2,6 1Department of Clinical Laboratory, Shanghai Children’s Hospital, Shanghai Jiaotong University, Shanghai, China; 2Department of Respiratory, Shanghai Children’s Hospital, Shanghai Jiaotong University, Shanghai, China; 3Shanghai Personal Biotechnology Co., Ltd, Shanghai, China; 4Department of Medical Microbiology and Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China; 5Zhejiang Bioruida Biotechnology co. Ltd, Zhejiang, China; 6New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA Introduction: Multidrug resistance in Streptococcus pneumoniae has emerged as a serious problem to public health. A further understanding of the genetic diversity in antibiotic-resistant S. pneumoniae isolates is needed. Methods: We conducted whole-genome resequencing for 25 pneumococcal strains isolated from children with different antimicrobial resistance profiles. Comparative analysis focus on detection of single-nucleotide polymorphisms (SNPs and insertions and deletions (indels was conducted. Moreover, phylogenetic analysis was applied to investigate the genetic relationship among these strains. Results: The genome size of the isolates was ~2.1 Mbp, covering >90% of the total estimated size of the reference genome. The overall G+C% content was ~39.5%, and there were 2,200–2,400 open reading frames. All isolates with different drug resistance profiles harbored many indels (range 131–171 and SNPs (range 16,103–28,128. Genetic diversity analysis showed that the variation of different genes were associated with specific antibiotic resistance. Known antibiotic resistance genes (pbps, murMN, ciaH, rplD, sulA, and dpr were identified, and new genes (regR, argH, trkH, and PTS-EII closely related with antibiotic resistance were found, although these genes were primarily annotated

  19. Genomic analysis of mouse retinal development.

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    Seth Blackshaw

    2004-09-01

    Full Text Available The vertebrate retina is comprised of seven major cell types that are generated in overlapping but well-defined intervals. To identify genes that might regulate retinal development, gene expression in the developing retina was profiled at multiple time points using serial analysis of gene expression (SAGE. The expression patterns of 1,051 genes that showed developmentally dynamic expression by SAGE were investigated using in situ hybridization. A molecular atlas of gene expression in the developing and mature retina was thereby constructed, along with a taxonomic classification of developmental gene expression patterns. Genes were identified that label both temporal and spatial subsets of mitotic progenitor cells. For each developing and mature major retinal cell type, genes selectively expressed in that cell type were identified. The gene expression profiles of retinal Müller glia and mitotic progenitor cells were found to be highly similar, suggesting that Müller glia might serve to produce multiple retinal cell types under the right conditions. In addition, multiple transcripts that were evolutionarily conserved that did not appear to encode open reading frames of more than 100 amino acids in length ("noncoding RNAs" were found to be dynamically and specifically expressed in developing and mature retinal cell types. Finally, many photoreceptor-enriched genes that mapped to chromosomal intervals containing retinal disease genes were identified. These data serve as a starting point for functional investigations of the roles of these genes in retinal development and physiology.

  20. Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

    DEFF Research Database (Denmark)

    de Vries, Paul S; Sabater-Lleal, Maria; Chasman, Daniel I

    2017-01-01

    An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In...

  1. Survey sequencing and comparative analysis of the elephant shark (Callorhinchus milii genome.

    Directory of Open Access Journals (Sweden)

    Byrappa Venkatesh

    2007-04-01

    Full Text Available Owing to their phylogenetic position, cartilaginous fishes (sharks, rays, skates, and chimaeras provide a critical reference for our understanding of vertebrate genome evolution. The relatively small genome of the elephant shark, Callorhinchus milii, a chimaera, makes it an attractive model cartilaginous fish genome for whole-genome sequencing and comparative analysis. Here, the authors describe survey sequencing (1.4x coverage and comparative analysis of the elephant shark genome, one of the first cartilaginous fish genomes to be sequenced to this depth. Repetitive sequences, represented mainly by a novel family of short interspersed element-like and long interspersed element-like sequences, account for about 28% of the elephant shark genome. Fragments of approximately 15,000 elephant shark genes reveal specific examples of genes that have been lost differentially during the evolution of tetrapod and teleost fish lineages. Interestingly, the degree of conserved synteny and conserved sequences between the human and elephant shark genomes are higher than that between human and teleost fish genomes. Elephant shark contains putative four Hox clusters indicating that, unlike teleost fish genomes, the elephant shark genome has not experienced an additional whole-genome duplication. These findings underscore the importance of the elephant shark as a critical reference vertebrate genome for comparative analysis of the human and other vertebrate genomes. This study also demonstrates that a survey-sequencing approach can be applied productively for comparative analysis of distantly related vertebrate genomes.

  2. Synonymous Codon Usage Analysis of Thirty Two Mycobacteriophage Genomes

    Directory of Open Access Journals (Sweden)

    Sameer Hassan

    2009-01-01

    Full Text Available Synonymous codon usage of protein coding genes of thirty two completely sequenced mycobacteriophage genomes was studied using multivariate statistical analysis. One of the major factors influencing codon usage is identified to be compositional bias. Codons ending with either C or G are preferred in highly expressed genes among which C ending codons are highly preferred over G ending codons. A strong negative correlation between effective number of codons (Nc and GC3s content was also observed, showing that the codon usage was effected by gene nucleotide composition. Translational selection is also identified to play a role in shaping the codon usage operative at the level of translational accuracy. High level of heterogeneity is seen among and between the genomes. Length of genes is also identified to influence the codon usage in 11 out of 32 phage genomes. Mycobacteriophage Cooper is identified to be the highly biased genome with better translation efficiency comparing well with the host specific tRNA genes.

  3. Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

    Science.gov (United States)

    Yazar, Seyhan; Gooden, George E C; Mackey, David A; Hewitt, Alex W

    2014-01-01

    A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2) for E.coli and 53.5% (95% CI: 34.4-72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1) and 173.9% (95% CI: 134.6-213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

  4. The sequence and analysis of a Chinese pig genome

    Directory of Open Access Journals (Sweden)

    Fang Xiaodong

    2012-11-01

    Full Text Available Abstract Background The pig is an economically important food source, amounting to approximately 40% of all meat consumed worldwide. Pigs also serve as an important model organism because of their similarity to humans at the anatomical, physiological and genetic level, making them very useful for studying a variety of human diseases. A pig strain of particular interest is the miniature pig, specifically the Wuzhishan pig (WZSP, as it has been extensively inbred. Its high level of homozygosity offers increased ease for selective breeding for specific traits and a more straightforward understanding of the genetic changes that underlie its biological characteristics. WZSP also serves as a promising means for applications in surgery, tissue engineering, and xenotransplantation. Here, we report the sequencing and analysis of an inbreeding WZSP genome. Results Our results reveal some unique genomic features, including a relatively high level of homozygosity in the diploid genome, an unusual distribution of heterozygosity, an over-representation of tRNA-derived transposable elements, a small amount of porcine endogenous retrovirus, and a lack of type C retroviruses. In addition, we carried out systematic research on gene evolution, together with a detailed investigation of the counterparts of human drug target genes. Conclusion Our results provide the opportunity to more clearly define the genomic character of pig, which could enhance our ability to create more useful pig models.

  5. Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

    Directory of Open Access Journals (Sweden)

    Seyhan Yazar

    Full Text Available A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR on Amazon EC2 instances and Google Compute Engine (GCE, using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2 for E.coli and 53.5% (95% CI: 34.4-72.6 for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1 and 173.9% (95% CI: 134.6-213.1 more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

  6. Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

    Science.gov (United States)

    Ghosh, Debashis; Chinnaiyan, Arul M

    2009-01-01

    In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

  7. Ensembl Genomes 2016: more genomes, more complexity.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

    2016-01-04

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Sensitivity analysis for large-scale problems

    Science.gov (United States)

    Noor, Ahmed K.; Whitworth, Sandra L.

    1987-01-01

    The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.

  9. An Instructional Module on Mokken Scale Analysis

    Science.gov (United States)

    Wind, Stefanie A.

    2017-01-01

    Mokken scale analysis (MSA) is a probabilistic-nonparametric approach to item response theory (IRT) that can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. This instructional module provides an introduction to MSA as a probabilistic-nonparametric framework in which to explore…

  10. A case study for cloud based high throughput analysis of NGS data using the globus genomics system

    Directory of Open Access Journals (Sweden)

    Krithika Bhuvaneshwar

    2015-01-01

    Full Text Available Next generation sequencing (NGS technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.

  11. Dirofilaria immitis JYD-34 isolate: whole genome analysis

    Directory of Open Access Journals (Sweden)

    Catherine Bourguinat

    2017-11-01

    Full Text Available Abstract Background Macrocyclic lactone (ML anthelmintics are used for chemoprophylaxis for heartworm infection in dogs and cats. Cases of dogs becoming infected with heartworms, despite apparent compliance to recommended chemoprophylaxis with approved preventives, has led to such cases being considered as suspected lack of efficacy (LOE. Recently, microfilariae collected from a small number of LOE isolates were used as a source of infection of new host dogs and confirmed to have reduced susceptibility to ML in controlled efficacy studies using L3 challenge in dogs. A specific Dirofilaria immitis laboratory isolate named JYD-34 has also been confirmed to have less than 100% susceptibility to ML-based preventives. For preventive claims against heartworm disease, evidence of 100% efficacy is required by FDA-CVM. It was therefore of interest to determine whether JYD-34 has a genetic profile similar to other documented LOE and confirmed reduced susceptibility isolates or has a genetic profile similar to known ML-susceptible isolates. Methods In this study, the 90Mbp whole genome of the JYD-34 strain was sequenced. This genome was compared using bioinformatics tools to pooled whole genomes of four well-characterized susceptible D. immitis populations, one susceptible Missouri laboratory isolate, as well as the pooled whole genomes of four LOE D. immitis populations. Fixation indexes (FST, which allow the genetic structure of each population (isolate to be compared at the level of single nucleotide polymorphisms (SNP across the genome, have been calculated. Forty-one previously reported SNP, that appeared to differentiate between susceptible and LOE and confirmed reduced susceptibility isolates, were also investigated in the JYD-34 isolate. Results The FST analysis, and the analysis of the 41 SNP that appeared to differentiate reduced susceptibility from fully susceptible isolates, confirmed that the JYD-34 isolate has a genome similar to previously

  12. Group sparse canonical correlation analysis for genomic data integration.

    Science.gov (United States)

    Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D; Deng, Hong-Wen; Wang, Yu-Ping

    2013-08-12

    The emergence of high-throughput genomic datasets from different sources and platforms (e.g., gene expression, single nucleotide polymorphisms (SNP), and copy number variation (CNV)) has greatly enhanced our understandings of the interplay of these genomic factors as well as their influences on the complex diseases. It is challenging to explore the relationship between these different types of genomic data sets. In this paper, we focus on a multivariate statistical method, canonical correlation analysis (CCA) method for this problem. Conventional CCA method does not work effectively if the number of data samples is significantly less than that of biomarkers, which is a typical case for genomic data (e.g., SNPs). Sparse CCA (sCCA) methods were introduced to overcome such difficulty, mostly using penalizations with l-1 norm (CCA-l1) or the combination of l-1and l-2 norm (CCA-elastic net). However, they overlook the structural or group effect within genomic data in the analysis, which often exist and are important (e.g., SNPs spanning a gene interact and work together as a group). We propose a new group sparse CCA method (CCA-sparse group) along with an effective numerical algorithm to study the mutual relationship between two different types of genomic data (i.e., SNP and gene expression). We then extend the model to a more general formulation that can include the existing sCCA models. We apply the model to feature/variable selection from two data sets and compare our group sparse CCA method with existing sCCA methods on both simulation and two real datasets (human gliomas data and NCI60 data). We use a graphical representation of the samples with a pair of canonical variates to demonstrate the discriminating characteristic of the selected features. Pathway analysis is further performed for biological interpretation of those features. The CCA-sparse group method incorporates group effects of features into the correlation analysis while performs individual feature

  13. SIDEKICK: Genomic data driven analysis and decision-making framework

    Directory of Open Access Journals (Sweden)

    Yoon Kihoon

    2010-12-01

    Full Text Available Abstract Background Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation. Results Sidekick, a genomic data driven analysis and decision making framework, is a web-based tool that provides a user-friendly intuitive solution to the problem of information inaccessibility. Sidekick enables scientists without training in computation and data management to pursue answers to research questions like "What are the mechanisms for disease X" or "Does the set of genes associated with disease X also influence other diseases." Sidekick enables the process of combining heterogeneous data, finding and maintaining the most up-to-date data, evaluating data sources, quantifying confidence in results based on evidence, and managing the multi-step research tasks needed to answer these questions. We demonstrate Sidekick's effectiveness by showing how to accomplish a complex published analysis in a fraction of the original time with no computational effort using Sidekick. Conclusions Sidekick is an easy-to-use web-based tool that organizes and facilitates complex genomic research, allowing scientists to explore genomic relationships and formulate hypotheses without computational effort. Possible analysis steps include gene list discovery, gene-pair list discovery, various enrichments for both types of lists, and convenient list manipulation. Further, Sidekick's ability to characterize pairs of genes offers new ways to

  14. Genome-wide analysis of Tol2 transposon reintegration in zebrafish

    Directory of Open Access Journals (Sweden)

    Parinov Sergey

    2009-09-01

    Full Text Available Abstract Background Tol2, a member of the hAT family of transposons, has become a useful tool for genetic manipulation of model animals, but information about its interactions with vertebrate genomes is still limited. Furthermore, published reports on Tol2 have mainly been based on random integration of the transposon system after co-injection of a plasmid DNA harboring the transposon and a transposase mRNA. It is important to understand how Tol2 would behave upon activation after integration into the genome. Results We performed a large-scale enhancer trap (ET screen and generated 338 insertions of the Tol2 transposon-based ET cassette into the zebrafish genome. These insertions were generated by remobilizing the transposon from two different donor sites in two transgenic lines. We found that 39% of Tol2 insertions occurred in transcription units, mostly into introns. Analysis of the transposon target sites revealed no strict specificity at the DNA sequence level. However, Tol2 was prone to target AT-rich regions with weak palindromic consensus sequences centered at the insertion site. Conclusion Our systematic analysis of sequential remobilizations of the Tol2 transposon from two independent sites within a vertebrate genome has revealed properties such as a tendency to integrate into transcription units and into AT-rich palindrome-like sequences. This information will influence the development of various applications involving DNA transposons and Tol2 in particular.

  15. Genome-wide analysis of Tol2 transposon reintegration in zebrafish.

    Science.gov (United States)

    Kondrychyn, Igor; Garcia-Lecea, Marta; Emelyanov, Alexander; Parinov, Sergey; Korzh, Vladimir

    2009-09-08

    Tol2, a member of the hAT family of transposons, has become a useful tool for genetic manipulation of model animals, but information about its interactions with vertebrate genomes is still limited. Furthermore, published reports on Tol2 have mainly been based on random integration of the transposon system after co-injection of a plasmid DNA harboring the transposon and a transposase mRNA. It is important to understand how Tol2 would behave upon activation after integration into the genome. We performed a large-scale enhancer trap (ET) screen and generated 338 insertions of the Tol2 transposon-based ET cassette into the zebrafish genome. These insertions were generated by remobilizing the transposon from two different donor sites in two transgenic lines. We found that 39% of Tol2 insertions occurred in transcription units, mostly into introns. Analysis of the transposon target sites revealed no strict specificity at the DNA sequence level. However, Tol2 was prone to target AT-rich regions with weak palindromic consensus sequences centered at the insertion site. Our systematic analysis of sequential remobilizations of the Tol2 transposon from two independent sites within a vertebrate genome has revealed properties such as a tendency to integrate into transcription units and into AT-rich palindrome-like sequences. This information will influence the development of various applications involving DNA transposons and Tol2 in particular.

  16. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    NARCIS (Netherlands)

    Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J.; Maranian, Mel J.; Bolla, Manjeet K.; Wang, Qin; Shah, Mitul; Perkins, Barbara J.; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S.; Bojesen, Stig E.; Nordestgaard, Borge G.; Flyger, Henrik; Nielsen, Sune F.; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A.; Aittomaki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G.; Whittemore, Alice S.; John, Esther M.; Malone, Kathleen E.; Gammon, Marilie D.; Santella, Regina M.; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F.; Casey, Graham; Hunter, David J.; Gapstur, Susan M.; Gaudet, Mia M.; Diver, W. Ryan; Haiman, Christopher A.; Schumacher, Fredrick; Henderson, Brian E.; Le Marchand, Loic; Berg, Christine D.; Chanock, Stephen J.; Figueroa, Jonine; Hoover, Robert N.; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K.; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J.; Olson, Janet E.; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A.; van der Luijt, Rob B.; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guenel, Pascal; Truong, Therese; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H.; Tseng, Chiu-chen; Van den Berg, David; Stram, Daniel O.; Gonzalez-Neira, Anna; Benitez, Javier; Zamora, M. Pilar; Arias Perez, Jose Ignacio; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; Tan, Gie-Hooi; Hooning, Maartje J.; Hollestelle, Antoinette; Martens, John W. M.; Collee, J. Margriet; Blot, William; Signorello, Lisa B.; Cai, Qiuyin; Hopper, John L.; Southey, Melissa C.; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N.; Nord, Silje; Alnaes, Grethe I. Grenaker; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Canzian, Federico; Trichopoulos, Dimitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J.; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K.; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A.; Hein, Alexander; Beckmann, Matthias W.; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J.; Swerdlow, Anthony J.; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L.; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S.; Labreche, France; Dumont, Martine; Winqvist, Robert; Pylkas, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Bruening, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V.; Doerk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Devilee, Peter; Tollenaar, Robert A. E. M.; Seynaeve, Caroline; Van Asperen, Christi J.; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; Mckay, James; Slager, Susan; Toland, Amanda E.; Ambrosone, Christine B.; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L.; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S.; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Rosario Alonso, M.; Alvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul P. D. P.; Kraft, Peter; Dunning, Alison M.; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F.

    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining similar to 14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising

  17. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    NARCIS (Netherlands)

    K. Michailidou (Kyriaki); J. Beesley (Jonathan); S. Lindstrom (Stephen); S. Canisius (Sander); J. Dennis (Joe); M. Lush (Michael); M. Maranian (Melanie); M.K. Bolla (Manjeet); Q. Wang (Qing); M. Shah (Mitul); B. Perkins (Barbara); K. Czene (Kamila); M. Eriksson (Mikael); H. Darabi (Hatef); J.S. Brand (Judith S.); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); H. Flyger (Henrik); S.F. Nielsen (Sune); N. Rahman (Nazneen); C. Turnbull (Clare); O. Fletcher (Olivia); J. Peto (Julian); L.J. Gibson (Lorna); I. dos Santos Silva (Isabel); J. Chang-Claude (Jenny); D. Flesch-Janys (Dieter); A. Rudolph (Anja); U. Eilber (Ursula); T.W. Behrens (Timothy); H. Nevanlinna (Heli); T.A. Muranen (Taru); K. Aittomäki (Kristiina); C. Blomqvist (Carl); S. Khan (Sofia); K. Aaltonen (Kirsimari); H. Ahsan (Habibul); M.G. Kibriya (Muhammad); A.S. Whittemore (Alice S.); E.M. John (Esther M.); K.E. Malone (Kathleen E.); M.D. Gammon (Marilie); R.M. Santella (Regina M.); G. Ursin (Giske); E. Makalic (Enes); D.F. Schmidt (Daniel); G. Casey (Graham); D.J. Hunter (David J.); S.M. Gapstur (Susan M.); M.M. Gaudet (Mia); W.R. Diver (Ryan); C.A. Haiman (Christopher A.); F.R. Schumacher (Fredrick); B.E. Henderson (Brian); L. Le Marchand (Loic); C.D. Berg (Christine); S.J. Chanock (Stephen); J.D. Figueroa (Jonine); R.N. Hoover (Robert N.); D. Lambrechts (Diether); P. Neven (Patrick); H. Wildiers (Hans); E. van Limbergen (Erik); M.K. Schmidt (Marjanka); A. Broeks (Annegien); S. Verhoef; S. Cornelissen (Sten); F.J. Couch (Fergus); J.E. Olson (Janet); B. Hallberg (Boubou); C. Vachon (Celine); Q. Waisfisz (Quinten); E.J. Meijers-Heijboer (Hanne); M.A. Adank (Muriel); R.B. van der Luijt (Rob); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); D. Kang (Daehee); J.-Y. Choi (Ji-Yeob); S.K. Park (Sue K.); K.Y. Yoo; K. Matsuo (Keitaro); H. Ito (Hidemi); H. Iwata (Hiroji); K. Tajima (Kazuo); P. Guénel (Pascal); T. Truong (Thérèse); C. Mulot (Claire); M. Sanchez (Marie); B. Burwinkel (Barbara); F. Marme (Federick); H. Surowy (Harald); C. Sohn (Christof); A.H. Wu (Anna H); C.-C. Tseng (Chiu-chen); D. Van Den Berg (David); D.O. Stram (Daniel O.); A. González-Neira (Anna); J. Benítez (Javier); M.P. Zamora (Pilar); J.I.A. Perez (Jose Ignacio Arias); X.-O. Shu (Xiao-Ou); W. Lu (Wei); Y. Gao; H. Cai (Hui); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); A.-M. Mulligan (Anna-Marie); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); A. Lindblom (Annika); S. Margolin (Sara); S.H. Teo (Soo Hwang); C.H. Yip (Cheng Har); N.A.M. Taib (Nur Aishah Mohd); G.-H. Tan (Gie-Hooi); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); J.W.M. Martens (John); J.M. Collée (Margriet); W.J. Blot (William); L.B. Signorello (Lisa B.); Q. Cai (Qiuyin); J. Hopper (John); M.C. Southey (Melissa); H. Tsimiklis (Helen); C. Apicella (Carmel); C-Y. Shen (Chen-Yang); C.-N. Hsiung (Chia-Ni); P.-E. Wu (Pei-Ei); M.-F. Hou (Ming-Feng); V. Kristensen (Vessela); S. Nord (Silje); G.G. Alnæs (Grethe); G.G. Giles (Graham G.); R.L. Milne (Roger); C.A. McLean (Catriona Ann); F. Canzian (Federico); D. Trichopoulos (Dimitrios); P.H.M. Peeters; E. Lund (Eiliv); R. Sund (Reijo); K.T. Khaw; M.J. Gunter (Marc J.); D. Palli (Domenico); L.M. Mortensen (Lotte Maxild); L. Dossus (Laure); J.-M. Huerta (Jose-Maria); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Sutter (Christian); R. Yang (Rongxi); K. Muir (Kenneth); A. Lophatananon (Artitaya); S. Stewart-Brown (Sarah); P. Siriwanarangsan (Pornthep); J.M. Hartman (Joost); X. Miao; K.S. Chia (Kee Seng); C.W. Chan (Ching Wan); P.A. Fasching (Peter); R. Hein (Rebecca); M.W. Beckmann (Matthias); L. Haeberle (Lothar); H. Brenner (Hermann); A.K. Dieffenbach (Aida Karina); V. Arndt (Volker); C. Stegmaier (Christa); A. Ashworth (Alan); N. Orr (Nick); M. Schoemaker (Minouk); A.J. Swerdlow (Anthony ); L.A. Brinton (Louise); M. García-Closas (Montserrat); W. Zheng (Wei); S.L. Halverson (Sandra L.); M. Shrubsole (Martha); J. Long (Jirong); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); H. Brauch (Hiltrud); U. Hamann (Ute); T. Brüning (Thomas); P. Radice (Paolo); P. Peterlongo (Paolo); S. Manoukian (Siranoush); L. Bernard (Loris); N.V. Bogdanova (Natalia); T. Dörk (Thilo); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); P. Devilee (Peter); R.A.E.M. Tollenaar (Rob); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska (Katarzyna); T. Huzarski (Tomasz); S. Sangrajrang (Suleeporn); V. Gaborieau (Valerie); P. Brennan (Paul); J.D. McKay (James); S. Slager (Susan); A.E. Toland (Amanda); C.B. Ambrosone (Christine); D. Yannoukakos (Drakoulis); M. Kabisch (Maria); D. Torres (Diana); S.L. Neuhausen (Susan); H. Anton-Culver (Hoda); C. Luccarini (Craig); C. Baynes (Caroline); S. Ahmed (Shahana); S. Healey (Sue); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); G. Pita (Guillermo); M.R. Alonso (Rosario); N. Álvarez (Nuria); D. Herrero (Daniel); J. Simard (Jacques); P.P.D.P. Pharoah (Paul P.D.P.); P. Kraft (Peter); A.M. Dunning (Alison); G. Chenevix-Trench (Georgia); P. Hall (Per); D.F. Easton (Douglas)

    2015-01-01

    textabstractGenome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS,

  18. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara

    2015-01-01

    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748...

  19. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  20. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

    Science.gov (United States)

    Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

    2011-07-26

    Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  1. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    Science.gov (United States)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

  2. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows

    Directory of Open Access Journals (Sweden)

    Sztromwasser Paweł

    2011-06-01

    Full Text Available Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  3. Predicting growth of the healthy infant using a genome scale metabolic model.

    Science.gov (United States)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

  4. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  5. Genomic insight into the common carp (Cyprinus carpio genome by sequencing analysis of BAC-end sequences

    Directory of Open Access Journals (Sweden)

    Wang Jintu

    2011-04-01

    Full Text Available Abstract Background Common carp is one of the most important aquaculture teleost fish in the world. Common carp and other closely related Cyprinidae species provide over 30% aquaculture production in the world. However, common carp genomic resources are still relatively underdeveloped. BAC end sequences (BES are important resources for genome research on BAC-anchored genetic marker development, linkage map and physical map integration, and whole genome sequence assembling and scaffolding. Result To develop such valuable resources in common carp (Cyprinus carpio, a total of 40,224 BAC clones were sequenced on both ends, generating 65,720 clean BES with an average read length of 647 bp after sequence processing, representing 42,522,168 bp or 2.5% of common carp genome. The first survey of common carp genome was conducted with various bioinformatics tools. The common carp genome contains over 17.3% of repetitive elements with GC content of 36.8% and 518 transposon ORFs. To identify and develop BAC-anchored microsatellite markers, a total of 13,581 microsatellites were detected from 10,355 BES. The coding region of 7,127 genes were recognized from 9,443 BES on 7,453 BACs, with 1,990 BACs have genes on both ends. To evaluate the similarity to the genome of closely related zebrafish, BES of common carp were aligned against zebrafish genome. A total of 39,335 BES of common carp have conserved homologs on zebrafish genome which demonstrated the high similarity between zebrafish and common carp genomes, indicating the feasibility of comparative mapping between zebrafish and common carp once we have physical map of common carp. Conclusion BAC end sequences are great resources for the first genome wide survey of common carp. The repetitive DNA was estimated to be approximate 28% of common carp genome, indicating the higher complexity of the genome. Comparative analysis had mapped around 40,000 BES to zebrafish genome and established over 3

  6. Genomic insight into the common carp (Cyprinus carpio) genome by sequencing analysis of BAC-end sequences

    Science.gov (United States)

    2011-01-01

    Background Common carp is one of the most important aquaculture teleost fish in the world. Common carp and other closely related Cyprinidae species provide over 30% aquaculture production in the world. However, common carp genomic resources are still relatively underdeveloped. BAC end sequences (BES) are important resources for genome research on BAC-anchored genetic marker development, linkage map and physical map integration, and whole genome sequence assembling and scaffolding. Result To develop such valuable resources in common carp (Cyprinus carpio), a total of 40,224 BAC clones were sequenced on both ends, generating 65,720 clean BES with an average read length of 647 bp after sequence processing, representing 42,522,168 bp or 2.5% of common carp genome. The first survey of common carp genome was conducted with various bioinformatics tools. The common carp genome contains over 17.3% of repetitive elements with GC content of 36.8% and 518 transposon ORFs. To identify and develop BAC-anchored microsatellite markers, a total of 13,581 microsatellites were detected from 10,355 BES. The coding region of 7,127 genes were recognized from 9,443 BES on 7,453 BACs, with 1,990 BACs have genes on both ends. To evaluate the similarity to the genome of closely related zebrafish, BES of common carp were aligned against zebrafish genome. A total of 39,335 BES of common carp have conserved homologs on zebrafish genome which demonstrated the high similarity between zebrafish and common carp genomes, indicating the feasibility of comparative mapping between zebrafish and common carp once we have physical map of common carp. Conclusion BAC end sequences are great resources for the first genome wide survey of common carp. The repetitive DNA was estimated to be approximate 28% of common carp genome, indicating the higher complexity of the genome. Comparative analysis had mapped around 40,000 BES to zebrafish genome and established over 3,100 microsyntenies, covering over 50% of

  7. Comparative analysis of Acinetobacters: three genomes for three lifestyles.

    Directory of Open Access Journals (Sweden)

    David Vallenet

    Full Text Available Acinetobacter baumannii is the source of numerous nosocomial infections in humans and therefore deserves close attention as multidrug or even pandrug resistant strains are increasingly being identified worldwide. Here we report the comparison of two newly sequenced genomes of A. baumannii. The human isolate A. baumannii AYE is multidrug resistant whereas strain SDF, which was isolated from body lice, is antibiotic susceptible. As reference for comparison in this analysis, the genome of the soil-living bacterium A. baylyi strain ADP1 was used. The most interesting dissimilarities we observed were that i whereas strain AYE and A. baylyi genomes harbored very few Insertion Sequence elements which could promote expression of downstream genes, strain SDF sequence contains several hundred of them that have played a crucial role in its genome reduction (gene disruptions and simple DNA loss; ii strain SDF has low catabolic capacities compared to strain AYE. Interestingly, the latter has even higher catabolic capacities than A. baylyi which has already been reported as a very nutritionally versatile organism. This metabolic performance could explain the persistence of A. baumannii nosocomial strains in environments where nutrients are scarce; iii several processes known to play a key role during host infection (biofilm formation, iron uptake, quorum sensing, virulence factors were either different or absent, the best example of which is iron uptake. Indeed, strain AYE and A. baylyi use siderophore-based systems to scavenge iron from the environment whereas strain SDF uses an alternate system similar to the Haem Acquisition System (HAS. Taken together, all these observations suggest that the genome contents of the 3 Acinetobacters compared are partly shaped by life in distinct ecological niches: human (and more largely hospital environment, louse, soil.

  8. Genome sequencing and analysis of BCG vaccine strains.

    Directory of Open Access Journals (Sweden)

    Wen Zhang

    Full Text Available BACKGROUND: Although the Bacillus Calmette-Guérin (BCG vaccine against tuberculosis (TB has been available for more than 75 years, one third of the world's population is still infected with Mycobacterium tuberculosis and approximately 2 million people die of TB every year. To reduce this immense TB burden, a clearer understanding of the functional genes underlying the action of BCG and the development of new vaccines are urgently needed. METHODS AND FINDINGS: Comparative genomic analysis of 19 M. tuberculosis complex strains showed that BCG strains underwent repeated human manipulation, had higher region of deletion rates than those of natural M. tuberculosis strains, and lost several essential components such as T-cell epitopes. A total of 188 BCG strain T-cell epitopes were lost to various degrees. The non-virulent BCG Tokyo strain, which has the largest number of T-cell epitopes (359, lost 124. Here we propose that BCG strain protection variability results from different epitopes. This study is the first to present BCG as a model organism for genetics research. BCG strains have a very well-documented history and now detailed genome information. Genome comparison revealed the selection process of BCG strains under human manipulation (1908-1966. CONCLUSIONS: Our results revealed the cause of BCG vaccine strain protection variability at the genome level and supported the hypothesis that the restoration of lost BCG Tokyo epitopes is a useful future vaccine development strategy. Furthermore, these detailed BCG vaccine genome investigation results will be useful in microbial genetics, microbial engineering and other research fields.

  9. H2@Scale Resource and Market Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, Mark

    2017-07-12

    This presentation overviews progress to date on the H2@Scale resource and market analysis work. The work finds, for example, that hydrogen demand of 60 MMT/yr is possible when transportation and industry are considered; resources are available to meet that demand; using renewable resources would reduce emissions and fossil use by over 15%; further impacts are possible when considering synergistic benefits; additional analysis is underway to improve understanding of potential markets and synergistic impacts; and further analysis will be necessary to estimate impacts due to spatial characteristics, feedback effects in the economy, and inertia characteristics.

  10. YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia.

    Science.gov (United States)

    Tan, Shi Yang; Dutta, Avirup; Jakubovics, Nicholas S; Ang, Mia Yang; Siow, Cheuk Chuen; Mutha, Naresh Vr; Heydari, Hamed; Wee, Wei Yee; Wong, Guat Jah; Choo, Siew Woh

    2015-01-16

    Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity. To facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the

  11. St2-80: a new FISH marker for St genome and genome analysis in Triticeae.

    Science.gov (United States)

    Wang, Long; Shi, Qinghua; Su, Handong; Wang, Yi; Sha, Lina; Fan, Xing; Kang, Houyang; Zhang, Haiqin; Zhou, Yonghong

    2017-07-01

    The St genome is one of the most fundamental genomes in Triticeae. Repetitive sequences are widely used to distinguish different genomes or species. The primary objectives of this study were to (i) screen a new sequence that could easily distinguish the chromosome of the St genome from those of other genomes by fluorescence in situ hybridization (FISH) and (ii) investigate the genome constitution of some species that remain uncertain and controversial. We used degenerated oligonucleotide primer PCR (Dop-PCR), Dot-blot, and FISH to screen for a new marker of the St genome and to test the efficiency of this marker in the detection of the St chromosome at different ploidy levels. Signals produced by a new FISH marker (denoted St 2 -80) were present on the entire arm of chromosomes of the St genome, except in the centromeric region. On the contrary, St 2 -80 signals were present in the terminal region of chromosomes of the E, H, P, and Y genomes. No signal was detected in the A and B genomes, and only weak signals were detected in the terminal region of chromosomes of the D genome. St 2 -80 signals were obvious and stable in chromosomes of different genomes, whether diploid or polyploid. Therefore, St 2 -80 is a potential and useful FISH marker that can be used to distinguish the St genome from those of other genomes in Triticeae.

  12. Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling.

    Science.gov (United States)

    Niida, Atsushi; Nagayama, Satoshi; Miyano, Satoru; Mimori, Koshi

    2018-04-01

    Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle-level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  13. Genomic analysis of murine DNA-dependent protein kinase

    International Nuclear Information System (INIS)

    Fujimori, A.; Abe, M.

    2003-01-01

    Full text: The gene of catalytic subunit of DNA dependent protein kinase is responsible gene for SCID mice. The molecules play a critical role in non-homologous end joining including the V(D)J recombination. Contribution of the molecules to the difference of radiosensitivity and the susceptibility to cancer has been suggested. Here we show the entire nucleotide sequence of approximately 193 kbp and 84 kbp genomic regions encoding the entire DNA-PKcs gene in the mouse and chicken respectively. Retroposon was found in the intron 51 of mouse genomic DNA-PKcs gene but in human and chicken. Comparative analysis of these two species strongly suggested that only two genes, DNA-PKcs and MCM4, exist in the region of both species. Several conserved sequences and cis elements, however, were predicted. Recently, the orthologous region for the human DNA-PKcs locus was completed. The results of further comparative study will be discussed

  14. Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

    Directory of Open Access Journals (Sweden)

    Wenbo Tang

    Full Text Available Genome-wide association studies (GWAS have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function.We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1 in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis.The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7. In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8 at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively.In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function.

  15. Probing the genome-scale metabolic landscape of Bordetella pertussis, the causative agent of whooping cough.

    Science.gov (United States)

    Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe

    2017-08-25

    Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussi s. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content. IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis , and challenged its predictions

  16. Applications of Convex Analysis to Multidimensional Scaling

    OpenAIRE

    Jan de Leeuw

    2011-01-01

    In this paper we discuss the convergence of an algorithm for metric and nonmetric multidimensional scaling that is very similar to the C-matrix algorithm of Guttman. The paper improves some earlier results in two respects. In the first place the analysis is extended to cover general Minkovski metrics, in the second place a more elementary proof of convergence based on results of Robert is presented.

  17. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2017-01-01

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  18. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    KAUST Repository

    Hefzi, Hooman

    2016-11-23

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

  19. Genome-scale metabolic models applied to human health and disease.

    Science.gov (United States)

    Cook, Daniel J; Nielsen, Jens

    2017-11-01

    Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  20. iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

    Science.gov (United States)

    Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

    2018-01-01

    Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

  1. Comparative Genomic Analysis of Meningitis- and Bacteremia-Causing Pneumococci Identifies a Common Core Genome

    Science.gov (United States)

    Cornick, Jennifer E.; Chaguza, Chrispin; Yalcin, Feyruz; Harris, Simon R.; Gray, Katherine J.; Kiran, Anmol M.; Molyneux, Elizabeth; French, Neil; Faragher, Brian E.; Everett, Dean B.; Bentley, Stephen D.

    2015-01-01

    Streptococcus pneumoniae is a nasopharyngeal commensal that occasionally invades normally sterile sites to cause bloodstream infection and meningitis. Although the pneumococcal population structure and evolutionary genetics are well defined, it is not clear whether pneumococci that cause meningitis are genetically distinct from those that do not. Here, we used whole-genome sequencing of 140 isolates of S. pneumoniae recovered from bloodstream infection (n = 70) and meningitis (n = 70) to compare their genetic contents. By fitting a double-exponential decaying-function model, we show that these isolates share a core of 1,427 genes (95% confidence interval [CI], 1,425 to 1,435 genes) and that there is no difference in the core genome or accessory gene content from these disease manifestations. Gene presence/absence alone therefore does not explain the virulence behavior of pneumococci that reach the meninges. Our analysis, however, supports the requirement of a range of previously described virulence factors and vaccine candidates for both meningitis- and bacteremia-causing pneumococci. This high-resolution view suggests that, despite considerable competency for genetic exchange, all pneumococci are under considerable pressure to retain key components advantageous for colonization and transmission and that these components are essential for access to and survival in sterile sites. PMID:26259813

  2. Principles of proteome allocation are revealed using proteomic data and genome-scale models

    DEFF Research Database (Denmark)

    Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

    2016-01-01

    to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally...

  3. Bio-succinic acid production: Escherichia coli strains design from genome-scale perspectives

    Directory of Open Access Journals (Sweden)

    Bashir Sajo Mienda

    2017-10-01

    Full Text Available Escherichia coli (E. coli has been established to be a native producer of succinic acid (a platform chemical with different applications via mixed acid fermentation reactions. Genome-scale metabolic models (GEMs of E. coli have been published with capabilities of predicting strain design strategies for the production of bio-based succinic acid. Proof-of-principle strains are fundamentally constructed as a starting point for systems strategies for industrial strains development. Here, we review for the first time, the use of E. coli GEMs for construction of proof-of-principles strains for increasing succinic acid production. Specific case studies, where E. coli proof-of-principle strains were constructed for increasing bio-based succinic acid production from glucose and glycerol carbon sources have been highlighted. In addition, a propose systems strategies for industrial strain development that could be applicable for future microbial succinic acid production guided by GEMs have been presented.

  4. Reconstruction of genome-scale human metabolic models using omics data

    DEFF Research Database (Denmark)

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-01-01

    used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

  5. Construction of a plant-transformation-competent BIBAC library and genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.).

    Science.gov (United States)

    Lee, Mi-Kyung; Zhang, Yang; Zhang, Meiping; Goebel, Mark; Kim, Hee Jin; Triplett, Barbara A; Stelly, David M; Zhang, Hong-Bin

    2013-03-28

    . raimondii contains a D genome (D5). The library represents the first BIBAC library in cotton and related species, thus providing tools useful for integrative physical mapping, large-scale genome sequencing and large-scale functional analysis of the Upland cotton genome. Comparative sequence analysis provides insights into the Upland cotton genome, and a possible mechanism underlying the divergence and evolution of polyploid Upland cotton from its diploid putative progenitor species, G. raimondii.

  6. Comparative Genomic Analysis of Mannheimia haemolytica from Bovine Sources.

    Science.gov (United States)

    Klima, Cassidy L; Cook, Shaun R; Zaheer, Rahat; Laing, Chad; Gannon, Vick P; Xu, Yong; Rasmussen, Jay; Potter, Andrew; Hendrick, Steve; Alexander, Trevor W; McAllister, Tim A

    2016-01-01

    Bovine respiratory disease is a common health problem in beef production. The primary bacterial agent involved, Mannheimia haemolytica, is a target for antimicrobial therapy and at risk for associated antimicrobial resistance development. The role of M. haemolytica in pathogenesis is linked to serotype with serotypes 1 (S1) and 6 (S6) isolated from pneumonic lesions and serotype 2 (S2) found in the upper respiratory tract of healthy animals. Here, we sequenced the genomes of 11 strains of M. haemolytica, representing all three serotypes and performed comparative genomics analysis to identify genetic features that may contribute to pathogenesis. Possible virulence associated genes were identified within 14 distinct prophage, including a periplasmic chaperone, a lipoprotein, peptidoglycan glycosyltransferase and a stress response protein. Prophage content ranged from 2-8 per genome, but was higher in S1 and S6 strains. A type I-C CRISPR-Cas system was identified in each strain with spacer diversity and organization conserved among serotypes. The majority of spacers occur in S1 and S6 strains and originate from phage suggesting that serotypes 1 and 6 may be more resistant to phage predation. However, two spacers complementary to the host chromosome targeting a UDP-N-acetylglucosamine 2-epimerase and a glycosyl transferases group 1 gene are present in S1 and S6 strains only indicating these serotypes may employ CRISPR-Cas to regulate gene expression to avoid host immune responses or enhance adhesion during infection. Integrative conjugative elements are present in nine of the eleven genomes. Three of these harbor extensive multi-drug resistance cassettes encoding resistance against the majority of drugs used to combat infection in beef cattle, including macrolides and tetracyclines used in human medicine. The findings here identify key features that are likely contributing to serotype related pathogenesis and specific targets for vaccine design intended to reduce the

  7. Comparative Genomic Analysis of Mannheimia haemolytica from Bovine Sources.

    Directory of Open Access Journals (Sweden)

    Cassidy L Klima

    Full Text Available Bovine respiratory disease is a common health problem in beef production. The primary bacterial agent involved, Mannheimia haemolytica, is a target for antimicrobial therapy and at risk for associated antimicrobial resistance development. The role of M. haemolytica in pathogenesis is linked to serotype with serotypes 1 (S1 and 6 (S6 isolated from pneumonic lesions and serotype 2 (S2 found in the upper respiratory tract of healthy animals. Here, we sequenced the genomes of 11 strains of M. haemolytica, representing all three serotypes and performed comparative genomics analysis to identify genetic features that may contribute to pathogenesis. Possible virulence associated genes were identified within 14 distinct prophage, including a periplasmic chaperone, a lipoprotein, peptidoglycan glycosyltransferase and a stress response protein. Prophage content ranged from 2-8 per genome, but was higher in S1 and S6 strains. A type I-C CRISPR-Cas system was identified in each strain with spacer diversity and organization conserved among serotypes. The majority of spacers occur in S1 and S6 strains and originate from phage suggesting that serotypes 1 and 6 may be more resistant to phage predation. However, two spacers complementary to the host chromosome targeting a UDP-N-acetylglucosamine 2-epimerase and a glycosyl transferases group 1 gene are present in S1 and S6 strains only indicating these serotypes may employ CRISPR-Cas to regulate gene expression to avoid host immune responses or enhance adhesion during infection. Integrative conjugative elements are present in nine of the eleven genomes. Three of these harbor extensive multi-drug resistance cassettes encoding resistance against the majority of drugs used to combat infection in beef cattle, including macrolides and tetracyclines used in human medicine. The findings here identify key features that are likely contributing to serotype related pathogenesis and specific targets for vaccine design

  8. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.

    Science.gov (United States)

    Navone, Laura; McCubbin, Tim; Gonzalez-Garcia, Ricardo A; Nielsen, Lars K; Marcellin, Esteban

    2018-06-01

    Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp . shermanii and the pan- Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp . shermanii , two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  9. Transcriptome analysis reveals the time of the fourth round of genome duplication in common carp (Cyprinus carpio)

    Science.gov (United States)

    2012-01-01

    Background Common carp (Cyprinus carpio) is thought to have undergone one extra round of genome duplication compared to zebrafish. Transcriptome analysis has been used to study the existence and timing of genome duplication in species for which genome sequences are incomplete. Large-scale transcriptome data for the common carp genome should help reveal the timing of the additional duplication event. Results We have sequenced the transcriptome of common carp using 454 pyrosequencing. After assembling the 454 contigs and the published common carp sequences together, we obtained 49,669 contigs and identified genes using homology searches and an ab initio method. We identified 4,651 orthologous pairs between common carp and zebrafish and found 129,984 paralogous pairs within the common carp. An estimation of the synonymous substitution rate in the orthologous pairs indicated that common carp and zebrafish diverged 120 million years ago (MYA). We identified one round of genome duplication in common carp and estimated that it had occurred 5.6 to 11.3 MYA. In zebrafish, no genome duplication event after speciation was observed, suggesting that, compared to zebrafish, common carp had undergone an additional genome duplication event. We annotated the common carp contigs with Gene Ontology terms and KEGG pathways. Compared with zebrafish gene annotations, we found that a set of biological processes and pathways were enriched in common carp. Conclusions The assembled contigs helped us to estimate the time of the fourth-round of genome duplication in common carp. The resource that we have built as part of this study will help advance functional genomics and genome annotation studies in the future. PMID:22424280

  10. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

    Science.gov (United States)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-08-01

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

  11. A Genomic Survey of SCPP Family Genes in Fishes Provides Novel Insights into the Evolution of Fish Scales.

    Science.gov (United States)

    Lv, Yunyun; Kawasaki, Kazuhiko; Li, Jia; Li, Yanping; Bian, Chao; Huang, Yu; You, Xinxin; Shi, Qiong

    2017-11-16

    The family of secretory calcium-binding phosphoproteins (SCPPs) have been considered vital to skeletal tissue mineralization. However, most previous SCPP studies focused on phylogenetically distant animals but not on those closely related species. Here we provide novel insights into the coevolution of SCPP genes and fish scales in 10 species from Otophysi . According to their scale phenotypes, these fishes can be divided into three groups, i.e., scaled, sparsely scaled, and scaleless. We identified homologous SCPP genes in the genomes of these species and revealed an absence of some SCPP members in some genomes, suggesting an uneven evolutionary history of SCPP genes in fishes. In addition, most of these SCPP genes, with the exception of SPP1 , individually form one or two gene cluster(s) on each corresponding genome. Furthermore, we constructed phylogenetic trees using maximum likelihood method to estimate their evolution. The phylogenetic topology mostly supports two subclasses in some species, such as Cyprinus carpio , Sinocyclocheilus anshuiensis , S. grahamin , and S. rhinocerous , but not in the other examined fishes. By comparing the gene structures of recently reported candidate genes, SCPP1 and SCPP5 , for determining scale phenotypes, we found that the hypothesis is suitable for Astyanax mexicanus , but denied by S. anshuiensis , even though they are both sparsely scaled for cave adaptation. Thus, we conclude that, although different fish species display similar scale phenotypes, the underlying genetic changes however might be diverse. In summary, this paper accelerates the recognition of the SCPP family in teleosts for potential scale evolution.

  12. Fungal Genomics Program

    Energy Technology Data Exchange (ETDEWEB)

    Grigoriev, Igor

    2012-03-12

    The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scale genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.

  13. Recombination analysis based on the complete genome of bocavirus

    Directory of Open Access Journals (Sweden)

    Chen Shengxia

    2011-04-01

    Full Text Available Abstract Bocavirus include bovine parvovirus, minute virus of canine, porcine bocavirus, gorilla bocavirus, and Human bocaviruses 1-4 (HBoVs. Although recent reports showed that recombination happened in bocavirus, no systematical study investigated the recombination of bocavirus. The present study performed the phylogenetic and recombination analysis of bocavirus over the complete genomes available in GenBank. Results confirmed that recombination existed among bocavirus, including the likely inter-genotype recombination between HBoV1 and HBoV4, and intra-genotype recombination among HBoV2 variants. Moreover, it is the first report revealing the recombination that occurred between minute viruses of canine.

  14. Construction of an integrated database to support genomic sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gilbert, W.; Overbeek, R.

    1994-11-01

    The central goal of this project is to develop an integrated database to support comparative analysis of genomes including DNA sequence data, protein sequence data, gene expression data and metabolism data. In developing the logic-based system GenoBase, a broader integration of available data was achieved due to assistance from collaborators. Current goals are to easily include new forms of data as they become available and to easily navigate through the ensemble of objects described within the database. This report comments on progress made in these areas.

  15. Analysis Of Segmental Duplications In The Pig Genome Based On Next-Generation Sequencing

    DEFF Research Database (Denmark)

    Fadista, João; Bendixen, Christian

    Segmental duplications are >1kb segments of duplicated DNA present in a genome with high sequence identity (>90%). They are associated with genomic rearrangements and provide a significant source of gene and genome evolution within mammalian genomes. Although segmental duplications have been...... extensively studied in other organisms, its analysis in pig has been hampered by the lack of a complete pig genome assembly. By measuring the depth of coverage of Illumina whole-genome shotgun sequencing reads of the Tabasco animal aligned to the latest pig genome assembly (Sus scrofa 10 – based also...... and their associated copy number alterations, focusing on the global organization of these segments and their possible functional significance in porcine phenotypes. This work provides insights into mammalian genome evolution and generates a valuable resource for porcine genomics research...

  16. CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

    Science.gov (United States)

    Lee, Mikyung; Kim, Yangseok

    2009-12-16

    Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square

  17. Genomic analysis of primordial dwarfism reveals novel disease genes.

    Science.gov (United States)

    Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S

    2014-02-01

    Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis.

  18. Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Chen Jiun-Ching

    2007-05-01

    Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through

  19. Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

    Science.gov (United States)

    Xu, Kelin; Jin, Li; Xiong, Momiao

    2017-05-18

    Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction

  20. Microbial Genome Analysis and Comparisons: Web-based Protocols and Resources

    Science.gov (United States)

    Fully annotated genome sequences of many microorganisms are publicly available as a resource. However, in-depth analysis of these genomes using specialized tools is required to derive meaningful information. We describe here the utility of three powerful publicly available genome databases and ana...

  1. IMG 4 version of the integrated microbial genomes comparative analysis system

    Science.gov (United States)

    Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N.; Kyrpides, Nikos C.

    2014-01-01

    The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu). PMID:24165883

  2. IMG 4 version of the integrated microbial genomes comparative analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Markowitz, Victor M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Chen, I-Min A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Palaniappan, Krishna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Chu, Ken [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Szeto, Ernest [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Pillay, Manoj [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Ratner, Anna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Huang, Jinghua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Woyke, Tanja [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Huntemann, Marcel [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Anderson, Iain [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Billis, Konstantinos [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Varghese, Neha [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Mavromatis, Konstantinos [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Pati, Amrita [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Ivanova, Natalia N. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Kyrpides, Nikos C. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program

    2013-10-27

    The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Finally, different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

  3. Comparative Genomics and Transcriptomic Analysis of Mycobacterium Kansasii

    KAUST Repository

    Alzahid, Yara

    2014-04-01

    The group of Mycobacteria is one of the most intensively studied bacterial taxa, as they cause the two historical and worldwide known diseases: leprosy and tuberculosis. Mycobacteria not identified as tuberculosis or leprosy complex, have been referred to by ‘environmental mycobacteria’ or ‘Nontuberculous mycobacteria (NTM). Mycobacterium kansasii (M. kansasii) is one of the most frequent NTM pathogens, as it causes pulmonary disease in immuno-competent patients and pulmonary, and disseminated disease in patients with various immuno-deficiencies. There have been five documented subtypes of this bacterium, by different molecular typing methods, showing that type I causes tuberculosis-like disease in healthy individuals, and type II in immune-compromised individuals. The remaining types are said to be environmental, thereby, not causing any diseases. The aim of this project was to conduct a comparative genomic study of M. kansasii types I-V and investigating the gene expression level of those types. From various comparative genomics analysis, provided genomics evidence on why M. kansasii type I is considered pathogenic, by focusing on three key elements that are involved in virulence of Mycobacteria: ESX secretion system, Phospholipase c (plcb) and Mammalian cell entry (Mce) operons. The results showed the lack of the espA operon in types II-V, which renders the ESX- 1 operon dysfunctional, as espA is one of the key factors that control this secretion system. However, gene expression analysis showed this operon to be deleted in types II, III and IV. Furthermore, plcB was found to be truncated in types III and IV. Analysis of Mce operons (1-4) show that mce-1 operon is duplicated, mce-2 is absent and mce-3 and mce-4 is present in one copy in M. kansasii types I-V. Gene expression profiles of type I-IV, showed that the secreted proteins of ESX-1 were slightly upregulated in types II-IV when compared to type I and the secreted forms of ESX-5 were highly down

  4. GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

    Science.gov (United States)

    Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

    2006-03-31

    Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

  5. Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

    Directory of Open Access Journals (Sweden)

    Zhongqi Ge

    2018-04-01

    Full Text Available Summary: Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies. : Ge et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to provide a comprehensive characterization of the ubiquitin pathway. They detect somatic driver candidates in the ubiquitin pathway and identify a cluster of patients with poor survival, highlighting the importance of this pathway in cancer development. Keywords: ubiquitin pathway, pan-cancer analysis, The Cancer Genome Atlas, tumor subtype, cancer prognosis, therapeutic targets, biomarker, FBXW7

  6. Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

    Directory of Open Access Journals (Sweden)

    In Young Choi

    2013-12-01

    Full Text Available The advances in electronic medical records (EMRs and bioinformatics (BI represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

  7. Determining the control circuitry of redox metabolism at the genome-scale.

    Directory of Open Access Journals (Sweden)

    Stephen Federowicz

    2014-04-01

    Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

  8. The population genomics of begomoviruses: global scale population structure and gene flow

    Directory of Open Access Journals (Sweden)

    Prasanna HC

    2010-09-01

    Full Text Available Abstract Background The rapidly growing availability of diverse full genome sequences from across the world is increasing the feasibility of studying the large-scale population processes that underly observable pattern of virus diversity. In particular, characterizing the genetic structure of virus populations could potentially reveal much about how factors such as geographical distributions, host ranges and gene flow between populations combine to produce the discontinuous patterns of genetic diversity that we perceive as distinct virus species. Among the richest and most diverse full genome datasets that are available is that for the dicotyledonous plant infecting genus, Begomovirus, in the Family Geminiviridae. The begomoviruses all share the same whitefly vector, are highly recombinogenic and are distributed throughout tropical and subtropical regions where they seriously threaten the food security of the world's poorest people. Results We focus here on using a model-based population genetic approach to identify the genetically distinct sub-populations within the global begomovirus meta-population. We demonstrate the existence of at least seven major sub-populations that can further be sub-divided into as many as thirty four significantly differentiated and genetically cohesive minor sub-populations. Using the population structure framework revealed in the present study, we further explored the extent of gene flow and recombination between genetic populations. Conclusions Although geographical barriers are apparently the most significant underlying cause of the seven major population sub-divisions, within the framework of these sub-divisions, we explore patterns of gene flow to reveal that both host range differences and genetic barriers to recombination have probably been major contributors to the minor population sub-divisions that we have identified. We believe that the global Begomovirus population structure revealed here could

  9. The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

    DEFF Research Database (Denmark)

    Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin

    2015-01-01

    DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

  10. Large Scale EOF Analysis of Climate Data

    Science.gov (United States)

    Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.

    2016-12-01

    We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.

  11. Analysis of the Complete Mitochondrial Genome Sequence of the Diploid Cotton Gossypium raimondii by Comparative Genomics Approaches

    Directory of Open Access Journals (Sweden)

    Changwei Bi

    2016-01-01

    Full Text Available Cotton is one of the most important economic crops and the primary source of natural fiber and is an important protein source for animal feed. The complete nuclear and chloroplast (cp genome sequences of G. raimondii are already available but not mitochondria. Here, we assembled the complete mitochondrial (mt DNA sequence of G. raimondii into a circular genome of length of 676,078 bp and performed comparative analyses with other higher plants. The genome contains 39 protein-coding genes, 6 rRNA genes, and 25 tRNA genes. We also identified four larger repeats (63.9 kb, 10.6 kb, 9.1 kb, and 2.5 kb in this mt genome, which may be active in intramolecular recombination in the evolution of cotton. Strikingly, nearly all of the G. raimondii mt genome has been transferred to nucleus on Chr1, and the transfer event must be very recent. Phylogenetic analysis reveals that G. raimondii, as a member of Malvaceae, is much closer to another cotton (G. barbadense than other rosids, and the clade formed by two Gossypium species is sister to Brassicales. The G. raimondii mt genome may provide a crucial foundation for evolutionary analysis, molecular biology, and cytoplasmic male sterility in cotton and other higher plants.

  12. Genomic analysis suggests higher susceptibility of children to air pollution

    DEFF Research Database (Denmark)

    van Leeuwen, Danitsja M; Pedersen, Marie; Hendriksen, Peter J M

    2008-01-01

    modulated gene expressions. In addition, gene expressions in both children and adults were investigated for associations with micronuclei frequencies. Both analysis approaches returned considerably more genes or gene groups and pathways that significantly differed between children from both regions than......Differences in biological responses to exposure to hazardous airborne substances between children and adults have been reported, suggesting children to be more susceptible. Aim of this study was to improve our understanding of differences in susceptibility in cancer risk associated with air...... pollution by comparing genome-wide gene expression profiles in peripheral blood of children and their parents. Gene expression analysis was performed in blood from children and parents living in two different regions in the Czech Republic with different levels of air pollution. Data were analyzed by two...

  13. Use of application containers and workflows for genomic data analysis

    Directory of Open Access Journals (Sweden)

    Wade L Schulz

    2016-01-01

    Full Text Available Background: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. Methods: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. Results: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS data. Conclusions: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia.

  14. Use of application containers and workflows for genomic data analysis

    Science.gov (United States)

    Schulz, Wade L.; Durant, Thomas J. S.; Siddon, Alexa J.; Torres, Richard

    2016-01-01

    Background: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. Methods: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. Results: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data. Conclusions: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia. PMID:28163975

  15. Establishing a framework for comparative analysis of genome sequences

    Energy Technology Data Exchange (ETDEWEB)

    Bansal, A.K.

    1995-06-01

    This paper describes a framework and a high-level language toolkit for comparative analysis of genome sequence alignment The framework integrates the information derived from multiple sequence alignment and phylogenetic tree (hypothetical tree of evolution) to derive new properties about sequences. Multiple sequence alignments are treated as an abstract data type. Abstract operations have been described to manipulate a multiple sequence alignment and to derive mutation related information from a phylogenetic tree by superimposing parsimonious analysis. The framework has been applied on protein alignments to derive constrained columns (in a multiple sequence alignment) that exhibit evolutionary pressure to preserve a common property in a column despite mutation. A Prolog toolkit based on the framework has been implemented and demonstrated on alignments containing 3000 sequences and 3904 columns.

  16. Genome-wide analysis of regions similar to promoters of histone genes

    KAUST Repository

    Chowdhary, Rajesh

    2010-05-28

    Background: The purpose of this study is to: i) develop a computational model of promoters of human histone-encoding genes (shortly histone genes), an important class of genes that participate in various critical cellular processes, ii) use the model so developed to identify regions across the human genome that have similar structure as promoters of histone genes; such regions could represent potential genomic regulatory regions, e.g. promoters, of genes that may be coregulated with histone genes, and iii/ identify in this way genes that have high likelihood of being coregulated with the histone genes.Results: We successfully developed a histone promoter model using a comprehensive collection of histone genes. Based on leave-one-out cross-validation test, the model produced good prediction accuracy (94.1% sensitivity, 92.6% specificity, and 92.8% positive predictive value). We used this model to predict across the genome a number of genes that shared similar promoter structures with the histone gene promoters. We thus hypothesize that these predicted genes could be coregulated with histone genes. This hypothesis matches well with the available gene expression, gene ontology, and pathways data. Jointly with promoters of the above-mentioned genes, we found a large number of intergenic regions with similar structure as histone promoters.Conclusions: This study represents one of the most comprehensive computational analyses conducted thus far on a genome-wide scale of promoters of human histone genes. Our analysis suggests a number of other human genes that share a high similarity of promoter structure with the histone genes and thus are highly likely to be coregulated, and consequently coexpressed, with the histone genes. We also found that there are a large number of intergenic regions across the genome with their structures similar to promoters of histone genes. These regions may be promoters of yet unidentified genes, or may represent remote control regions that

  17. Genomic analysis of organismal complexity in the multicellular green alga Volvox carteri

    Energy Technology Data Exchange (ETDEWEB)

    Prochnik, Simon E.; Umen, James; Nedelcu, Aurora; Hallmann, Armin; Miller, Stephen M.; Nishii, Ichiro; Ferris, Patrick; Kuo, Alan; Mitros, Therese; Fritz-Laylin, Lillian K.; Hellsten, Uffe; Chapman, Jarrod; Simakov, Oleg; Rensing, Stefan A.; Terry, Astrid; Pangilinan, Jasmyn; Kapitonov, Vladimir; Jurka, Jerzy; Salamov, Asaf; Shapiro, Harris; Schmutz, Jeremy; Grimwood, Jane; Lindquist, Erika; Lucas, Susan; Grigoriev, Igor V.; Schmitt, Rudiger; Kirk, David; Rokhsar, Daniel S.

    2010-07-01

    Analysis of the Volvox carteri genome reveals that this green alga's increased organismal complexity and multicellularity are associated with modifications in protein families shared with its unicellular ancestor, and not with large-scale innovations in protein coding capacity. The multicellular green alga Volvox carteri and its morphologically diverse close relatives (the volvocine algae) are uniquely suited for investigating the evolution of multicellularity and development. We sequenced the 138 Mb genome of V. carteri and compared its {approx}14,500 predicted proteins to those of its unicellular relative, Chlamydomonas reinhardtii. Despite fundamental differences in organismal complexity and life history, the two species have similar protein-coding potentials, and few species-specific protein-coding gene predictions. Interestingly, volvocine algal-specific proteins are enriched in Volvox, including those associated with an expanded and highly compartmentalized extracellular matrix. Our analysis shows that increases in organismal complexity can be associated with modifications of lineage-specific proteins rather than large-scale invention of protein-coding capacity.

  18. CoryneCenter – An online resource for the integrated analysis of corynebacterial genome and transcriptome data

    Directory of Open Access Journals (Sweden)

    Hüser Andrea T

    2007-11-01

    Full Text Available Abstract Background The introduction of high-throughput genome sequencing and post-genome analysis technologies, e.g. DNA microarray approaches, has created the potential to unravel and scrutinize complex gene-regulatory networks on a large scale. The discovery of transcriptional regulatory interactions has become a major topic in modern functional genomics. Results To facilitate the analysis of gene-regulatory networks, we have developed CoryneCenter, a web-based resource for the systematic integration and analysis of genome, transcriptome, and gene regulatory information for prokaryotes, especially corynebacteria. For this purpose, we extended and combined the following systems into a common platform: (1 GenDB, an open source genome annotation system, (2 EMMA, a MAGE compliant application for high-throughput transcriptome data storage and analysis, and (3 CoryneRegNet, an ontology-based data warehouse designed to facilitate the reconstruction and analysis of gene regulatory interactions. We demonstrate the potential of CoryneCenter by means of an application example. Using microarray hybridization data, we compare the gene expression of Corynebacterium glutamicum under acetate and glucose feeding conditions: Known regulatory networks are confirmed, but moreover CoryneCenter points out additional regulatory interactions. Conclusion CoryneCenter provides more than the sum of its parts. Its novel analysis and visualization features significantly simplify the process of obtaining new biological insights into complex regulatory systems. Although the platform currently focusses on corynebacteria, the integrated tools are by no means restricted to these species, and the presented approach offers a general strategy for the analysis and verification of gene regulatory networks. CoryneCenter provides freely accessible projects with the underlying genome annotation, gene expression, and gene regulation data. The system is publicly available at http://www.CoryneCenter.de.

  19. Comparative genomic analysis of Vibrio parahaemolyticus: serotype conversion and virulence

    Directory of Open Access Journals (Sweden)

    Gil Ana I

    2011-06-01

    Full Text Available Abstract Background Vibrio parahaemolyticus is a common cause of foodborne disease. Beginning in 1996, a more virulent strain having serotype O3:K6 caused major outbreaks in India and other parts of the world, resulting in the emergence of a pandemic. Other serovariants of this strain emerged during its dissemination and together with the original O3:K6 were termed strains of the pandemic clone. Two genomes, one of this virulent strain and one pre-pandemic strain have been sequenced. We sequenced four additional genomes of V. parahaemolyticus in this study that were isolated from different geographical regions and time points. Comparative genomic analyses of six strains of V. parahaemolyticus isolated from Asia and Peru were performed in order to advance knowledge concerning the evolution of V. parahaemolyticus; specifically, the genetic changes contributing to serotype conversion and virulence. Two pre-pandemic strains and three pandemic strains, isolated from different geographical regions, were serotype O3:K6 and either toxin profiles (tdh+, trh- or (tdh-, trh+. The sixth pandemic strain sequenced in this study was serotype O4:K68. Results Genomic analyses revealed that the trh+ and tdh+ strains had different types of pathogenicity islands and mobile elements as well as major structural differences between the tdh pathogenicity islands of the pre-pandemic and pandemic strains. In addition, the results of single nucleotide polymorphism (SNP analysis showed that 94% of the SNPs between O3:K6 and O4:K68 pandemic isolates were within a 141 kb region surrounding the O- and K-antigen-encoding gene clusters. The "core" genes of V. parahaemolyticus were also compared to those of V. cholerae and V. vulnificus, in order to delineate differences between these three pathogenic species. Approximately one-half (49-59% of each species' core genes were conserved in all three species, and 14-24% of the core genes were species-specific and in different

  20. Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae : Implications for the microbial "pan-genome"

    NARCIS (Netherlands)

    Tettelin, H; Masignani, [No Value; Cieslewicz, MJ; Donati, C; Medini, D; Ward, NL; Angiuoli, SV; Crabtree, J; Jones, AL; Durkin, AS; DeBoy, RT; Davidsen, TM; Mora, M; Scarselli, M; Ros, IMY; Peterson, JD; Hauser, CR; Sundaram, JP; Nelson, WC; Madupu, R; Brinkac, LM; Dodson, RJ; Rosovitz, MJ; Sullivan, SA; Daugherty, SC; Haft, DH; Selengut, J; Gwinn, ML; Zhou, LW; Zafar, N; Khouri, H; Radune, D; Dimitrov, G; Watkins, K; O'Connor, KJB; Smith, S; Utterback, TR; White, O; Rubens, CE; Grandi, G; Madoff, LC; Kasper, DL; Telford, JL; Wessels, MR; Rappuoli, R; Fraser, CM

    2005-01-01

    The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and

  1. Genome-scale detection of positive selection in nine primates predicts human-virus evolutionary conflicts.

    Science.gov (United States)

    van der Lee, Robin; Wiel, Laurens; van Dam, Teunis J P; Huynen, Martijn A

    2017-10-13

    Hotspots of rapid genome evolution hold clues about human adaptation. We present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection in 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our new procedure is stringent and reveals substantial artefacts (20% of initial predictions) that have inflated previous estimates. The final 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immunity, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokines, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction and chromosome segregation (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors and mitochondrial proteins. Focusing on the virus-host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus-human interaction data. Protein structure analysis further identifies positive selection in the interaction interfaces between viruses and their cellular receptors (CD4-HIV; CD46-measles, adenoviruses; CD55-picornaviruses). Finally, primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positive selection is a rich source for studying the genetics underlying human (antiviral) phenotypes. Procedures and data are available at https://github.com/robinvanderlee/positive-selection. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. A Confirmatory Factor Analysis of Reilly's Role Overload Scale

    Science.gov (United States)

    Thiagarajan, Palaniappan; Chakrabarty, Subhra; Taylor, Ronald D.

    2006-01-01

    In 1982, Reilly developed a 13-item scale to measure role overload. This scale has been widely used, but most studies did not assess the unidimensionality of the scale. Given the significance of unidimensionality in scale development, the current study reports a confirmatory factor analysis of the 13-item scale in two samples. Based on the…

  3. The tiger genome and comparative analysis with lion and snow leopard genomes.

    Science.gov (United States)

    Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-Uk; Luo, Shu-Jin; Johnson, Warren E; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A; Marker, Laurie; Harper, Cindy; Miller, Susan M; Jacobs, Wilhelm; Bertola, Laura D; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O'Brien, Stephen J; Wang, Jun; Bhak, Jong

    2013-01-01

    Tigers and their close relatives (Panthera) are some of the world's most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats' hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species.

  4. The tiger genome and comparative analysis with lion and snow leopard genomes

    Science.gov (United States)

    Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-uk; Luo, Shu-Jin; Johnson, Warren E.; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A.; Marker, Laurie; Harper, Cindy; Miller, Susan M.; Jacobs, Wilhelm; Bertola, Laura D.; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O’Brien, Stephen J.; Wang, Jun; Bhak, Jong

    2013-01-01

    Tigers and their close relatives (Panthera) are some of the world’s most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats’ hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species. PMID:24045858

  5. Genome sequence analysis of the model grass Brachypodium distachyon: insights into grass genome evolution

    Energy Technology Data Exchange (ETDEWEB)

    Schulman, Al

    2009-08-09

    Three subfamilies of grasses, the Erhardtoideae (rice), the Panicoideae (maize, sorghum, sugar cane and millet), and the Pooideae (wheat, barley and cool season forage grasses) provide the basis of human nutrition and are poised to become major sources of renewable energy. Here we describe the complete genome sequence of the wild grass Brachypodium distachyon (Brachypodium), the first member of the Pooideae subfamily to be completely sequenced. Comparison of the Brachypodium, rice and sorghum genomes reveals a precise sequence- based history of genome evolution across a broad diversity of the grass family and identifies nested insertions of whole chromosomes into centromeric regions as a predominant mechanism driving chromosome evolution in the grasses. The relatively compact genome of Brachypodium is maintained by a balance of retroelement replication and loss. The complete genome sequence of Brachypodium, coupled to its exceptional promise as a model system for grass research, will support the development of new energy and food crops

  6. A scale-free structure prior for graphical models with applications in functional genomics.

    Directory of Open Access Journals (Sweden)

    Paul Sheridan

    Full Text Available The problem of reconstructing large-scale, gene regulatory networks from gene expression data has garnered considerable attention in bioinformatics over the past decade with the graphical modeling paradigm having emerged as a popular framework for inference. Analysis in a full Bayesian setting is contingent upon the assignment of a so-called structure prior-a probability distribution on networks, encoding a priori biological knowledge either in the form of supplemental data or high-level topological features. A key topological consideration is that a wide range of cellular networks are approximately scale-free, meaning that the fraction, , of nodes in a network with degree is roughly described by a power-law with exponent between and . The standard practice, however, is to utilize a random structure prior, which favors networks with binomially distributed degree distributions. In this paper, we introduce a scale-free structure prior for graphical models based on the formula for the probability of a network under a simple scale-free network model. Unlike the random structure prior, its scale-free counterpart requires a node labeling as a parameter. In order to use this prior for large-scale network inference, we design a novel Metropolis-Hastings sampler for graphical models that includes a node labeling as a state space variable. In a simulation study, we demonstrate that the scale-free structure prior outperforms the random structure prior at recovering scale-free networks while at the same time retains the ability to recover random networks. We then estimate a gene association network from gene expression data taken from a breast cancer tumor study, showing that scale-free structure prior recovers hubs, including the previously unknown hub SLC39A6, which is a zinc transporter that has been implicated with the spread of breast cancer to the lymph nodes. Our analysis of the breast cancer expression data underscores the value of the scale

  7. TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

    Science.gov (United States)

    Huang, Yen-Tsung; Hsu, Thomas; Christiani, David C

    2014-01-01

    The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X (2) distributions that can be obtained using permutation with scaled X (2) approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (number data, and causal mechanisms of the five pathways require further study.

  8. Research study on analysis/use technologies of genome information; Genome joho kaidoku riyo gijutsu no chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    For wide use of genome information in the industrial field, the required R and D was surveyed from the standpoints of biology and information science. To clarify the present state and issues of the international research on genome analysis, the genome map as well as sequence and function information are first surveyed. The current analysis/use technologies of genome information are analyzed, and the following are summarized: prediction and identification of gene regions in genome sequences, techniques for searching and selecting useful genes, and techniques for predicting the expression of gene functions and the gene-product structure and functions. It is recommended that R and D and data collection/interpretation necessary to clarify inter-gene interactions and information networks should be promoted by integrating Japanese advanced know-how and technologies. As examples of the impact of the research results on industry and society, the present state and future expected effect are summarized for medicines, diagnosis/analysis instruments, chemicals, foods, agriculture, fishery, animal husbandry, electronics, environment and information. 278 refs., 42 figs., 5 tabs.

  9. Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

    Directory of Open Access Journals (Sweden)

    Rachael Natrajan

    2016-02-01

    Full Text Available The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D in solid tumors, termed the tumor ecosystem diversity index (EDI, using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3 breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2 breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52. Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.To our knowledge, this is the first

  10. Comparative genomics analysis of rice and pineapple contributes to understand the chromosome number reduction and genomic changes in grasses

    Directory of Open Access Journals (Sweden)

    Jinpeng Wang

    2016-10-01

    Full Text Available Rice is one of the most researched model plant, and has a genome structure most resembling that of the grass common ancestor after a grass common tetraploidization ~100 million years ago. There has been a standing controversy whether there had been 5 or 7 basic chromosomes, before the tetraploidization, which were tackled but could not be well solved for the lacking of a sequenced and assembled outgroup plant to have a conservative genome structure. Recently, the availability of pineapple genome, which has not been subjected to the grass-common tetraploidization, provides a precious opportunity to solve the above controversy and to research into genome changes of rice and other grasses. Here, we performed a comparative genomics analysis of pineapple and rice, and found solid evidence that grass-common ancestor had 2n =2x =14 basic chromosomes before the tetraploidization and duplicated to 2n = 4x = 28 after the event. Moreover, we proposed that enormous gene missing from duplicated regions in rice should be explained by an allotetraploid produced by prominently divergent parental lines, rather than gene losses after their divergence. This means that genome fractionation might have occurred before the formation of the allotetraploid grass ancestor.

  11. Micron scale spectroscopic analysis of materials

    International Nuclear Information System (INIS)

    James, David; Finlayson, Trevor; Prawer, Steven

    1991-01-01

    The goal of this proposal is the establishment of a facility which will enable complete micron scale spectroscopic analysis of any sample which can be imaged in the optical microscope. Current applications include studies of carbon fibres, diamond thin films, ceramics (zirconia and high T c superconductors), semiconductors, wood pulp, wool fibres, mineral inclusions, proteins, plant cells, polymers, fluoride glasses, and optical fibres. The range of interests crosses traditional discipline boundaries and augurs well for a truly interdisciplinary collaboration. Developments in instrumentation such as confocal imaging are planned to achieve sub-micron resolution, and advances in computer software and hardware will enable the aforementioned spectroscopies to be used to map molecular and crystalline phases on the surfaces of materials. Coupled with existing compositional microprobes (e.g. the proton microprobe) the possibilities for the development of new, powerful, hybrid imaging technologies appear to be excellent

  12. Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

    Science.gov (United States)

    Rzhetsky, A; Gomez, S M

    2001-10-01

    Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

  13. Genome-wide analysis of wild-type Epstein-Barr virus genomes derived from healthy individuals of the 1,000 Genomes Project.

    Science.gov (United States)

    Santpere, Gabriel; Darre, Fleur; Blanco, Soledad; Alcami, Antonio; Villoslada, Pablo; Mar Albà, M; Navarro, Arcadi

    2014-04-01

    Most people in the world (∼90%) are infected by the Epstein-Barr virus (EBV), which establishes itself permanently in B cells. Infection by EBV is related to a number of diseases including infectious mononucleosis, multiple sclerosis, and different types of cancer. So far, only seven complete EBV strains have been described, all of them coming from donors presenting EBV-related diseases. To perform a detailed comparative genomic analysis of EBV including, for the first time, EBV strains derived from healthy individuals, we reconstructed EBV sequences infecting lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project. As strain B95-8 was used to transform B cells to obtain LCLs, it is always present, but a specific deletion in its genome sets it apart from natural EBV strains. After studying hundreds of individuals, we determined the presence of natural EBV in at least 10 of them and obtained a set of variants specific to wild-type EBV. By mapping the natural EBV reads into the EBV reference genome (NC007605), we constructed nearly complete wild-type viral genomes from three individuals. Adding them to the five disease-derived EBV genomic sequences available in the literature, we performed an in-depth comparative genomic analysis. We found that latency genes harbor more nucleotide diversity than lytic genes and that six out of nine latency-related genes, as well as other genes involved in viral attachment and entry into host cells, packaging, and the capsid, present the molecular signature of accelerated protein evolution rates, suggesting rapid host-parasite coevolution.

  14. Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

    Directory of Open Access Journals (Sweden)

    Jorge Fernandez-de-Cossio-Diaz

    2017-11-01

    Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

  15. BGI-RIS: an integrated information resource and comparative analysis workbench for rice genomics

    DEFF Research Database (Denmark)

    Zhao, Wenming; Wang, Jing; He, Ximiao

    2004-01-01

    Rice is a major food staple for the world's population and serves as a model species in cereal genome research. The Beijing Genomics Institute (BGI) has long been devoting itself to sequencing, information analysis and biological research of the rice and other crop genomes. In order to facilitate....... Designed as a basic platform, BGI-RIS presents the sequenced genomes and related information in systematic and graphical ways for the convenience of in-depth comparative studies (http://rise.genomics.org.cn/). Udgivelsesdato: 2004-Jan-1...

  16. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

    Science.gov (United States)

    2011-01-01

    Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

  17. Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

    Science.gov (United States)

    Chatterjee, Ankita; Kundu, Sudip

    2015-01-01

    Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104

  18. Novel insights into obesity and diabetes through genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    Leif eVäremo

    2013-04-01

    Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

  19. The Complete Chloroplast Genome of Catha edulis: A Comparative Analysis of Genome Features with Related Species

    Directory of Open Access Journals (Sweden)

    Cuihua Gu

    2018-02-01

    Full Text Available Qat (Catha edulis, Celastraceae is a woody evergreen species with great economic and cultural importance. It is cultivated for its stimulant alkaloids cathine and cathinone in East Africa and southwest Arabia. However, genome information, especially DNA sequence resources, for C. edulis are limited, hindering studies regarding interspecific and intraspecific relationships. Herein, the complete chloroplast (cp genome of Catha edulis is reported. This genome is 157,960 bp in length with 37% GC content and is structurally arranged into two 26,577 bp inverted repeats and two single-copy areas. The size of the small single-copy and the large single-copy regions were 18,491 bp and 86,315 bp, respectively. The C. edulis cp genome consists of 129 coding genes including 37 transfer RNA (tRNA genes, 8 ribosomal RNA (rRNA genes, and 84 protein coding genes. For those genes, 112 are single copy genes and 17 genes are duplicated in two inverted regions with seven tRNAs, four rRNAs, and six protein coding genes. The phylogenetic relationships resolved from the cp genome of qat and 32 other species confirms the monophyly of Celastraceae. The cp genomes of C. edulis, Euonymus japonicus and seven Celastraceae species lack the rps16 intron, which indicates an intron loss took place among an ancestor of this family. The cp genome of C. edulis provides a highly valuable genetic resource for further phylogenomic research, barcoding and cp transformation in Celastraceae.

  20. The Complete Chloroplast Genome of Catha edulis: A Comparative Analysis of Genome Features with Related Species

    Science.gov (United States)

    Tembrock, Luke R.; Zheng, Shaoyu; Wu, Zhiqiang

    2018-01-01

    Qat (Catha edulis, Celastraceae) is a woody evergreen species with great economic and cultural importance. It is cultivated for its stimulant alkaloids cathine and cathinone in East Africa and southwest Arabia. However, genome information, especially DNA sequence resources, for C. edulis are limited, hindering studies regarding interspecific and intraspecific relationships. Herein, the complete chloroplast (cp) genome of Catha edulis is reported. This genome is 157,960 bp in length with 37% GC content and is structurally arranged into two 26,577 bp inverted repeats and two single-copy areas. The size of the small single-copy and the large single-copy regions were 18,491 bp and 86,315 bp, respectively. The C. edulis cp genome consists of 129 coding genes including 37 transfer RNA (tRNA) genes, 8 ribosomal RNA (rRNA) genes, and 84 protein coding genes. For those genes, 112 are single copy genes and 17 genes are duplicated in two inverted regions with seven tRNAs, four rRNAs, and six protein coding genes. The phylogenetic relationships resolved from the cp genome of qat and 32 other species confirms the monophyly of Celastraceae. The cp genomes of C. edulis, Euonymus japonicus and seven Celastraceae species lack the rps16 intron, which indicates an intron loss took place among an ancestor of this family. The cp genome of C. edulis provides a highly valuable genetic resource for further phylogenomic research, barcoding and cp transformation in Celastraceae. PMID:29425128

  1. STINGRAY: system for integrated genomic resources and analysis.

    Science.gov (United States)

    Wagner, Glauber; Jardim, Rodrigo; Tschoeke, Diogo A; Loureiro, Daniel R; Ocaña, Kary A C S; Ribeiro, Antonio C B; Emmel, Vanessa E; Probst, Christian M; Pitaluga, André N; Grisard, Edmundo C; Cavalcanti, Maria C; Campos, Maria L M; Mattoso, Marta; Dávila, Alberto M R

    2014-03-07

    The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/.

  2. Functional Analysis of Shewanella, a cross genome comparison.

    Energy Technology Data Exchange (ETDEWEB)

    Serres, Margrethe H.

    2009-05-15

    The bacterial genus Shewanella includes a group of highly versatile organisms that have successfully adapted to life in many environments ranging from aquatic (fresh and marine) to sedimentary (lake and marine sediments, subsurface sediments, sea vent). A unique respiratory capability of the Shewanellas, initially observed for Shewanella oneidensis MR-1, is the ability to use metals and metalloids, including radioactive compounds, as electron acceptors. Members of the Shewanella genus have also been shown to degrade environmental pollutants i.e. halogenated compounds, making this group highly applicable for the DOE mission. S. oneidensis MR-1 has in addition been found to utilize a diverse set of nutrients and to have a large set of genes dedicated to regulation and to sensing of the environment. The sequencing of the S. oneidensis MR-1 genome facilitated experimental and bioinformatics analyses by a group of collaborating researchers, the Shewanella Federation. Through the joint effort and with support from Department of Energy S. oneidensis MR-1 has become a model organism of study. Our work has been a functional analysis of S. oneidensis MR-1, both by itself and as part of a comparative study. We have improved the annotation of gene products, assigned metabolic functions, and analyzed protein families present in S. oneidensis MR-1. The data has been applied to analysis of experimental data (i.e. gene expression, proteome) generated for S. oneidensis MR-1. Further, this work has formed the basis for a comparative study of over 20 members of the Shewanella genus. The species and strains selected for genome sequencing represented an evolutionary gradient of DNA relatedness, ranging from close to intermediate, and to distant. The organisms selected have also adapted to a variety of ecological niches. Through our work we have been able to detect and interpret genome similarities and differences between members of the genus. We have in this way contributed to the

  3. Sequencing and comparative genome analysis of two pathogenic Streptococcus gallolyticus subspecies: genome plasticity, adaptation and virulence.

    Directory of Open Access Journals (Sweden)

    I-Hsuan Lin

    Full Text Available Streptococcus gallolyticus infections in humans are often associated with bacteremia, infective endocarditis and colon cancers. The disease manifestations are different depending on the subspecies of S. gallolyticus causing the infection. Here, we present the complete genomes of S. gallolyticus ATCC 43143 (biotype I and S. pasteurianus ATCC 43144 (biotype II.2. The genomic differences between the two biotypes were characterized with comparative genomic analyses. The chromosome of ATCC 43143 and ATCC 43144 are 2,36 and 2,10 Mb in length and encode 2246 and 1869 CDS respectively. The organization and genomic contents of both genomes were most similar to the recently published S. gallolyticus UCN34, where 2073 (92% and 1607 (86% of the ATCC 43143 and ATCC 43144 CDS were conserved in UCN34 respectively. There are around 600 CDS conserved in all Streptococcus genomes, indicating the Streptococcus genus has a small core-genome (constitute around 30% of total CDS and substantial evolutionary plasticity. We identified eight and five regions of genome plasticity in ATCC 43143 and ATCC 43144 respectively. Within these regions, several proteins were recognized to contribute to the fitness and virulence of each of the two subspecies. We have also predicted putative cell-surface associated proteins that could play a role in adherence to host tissues, leading to persistent infections causing sub-acute and chronic diseases in humans. This study showed evidence that the S. gallolyticus still possesses genes making it suitable in a rumen environment, whereas the ability for S. pasteurianus to live in rumen is reduced. The genome heterogeneity and genetic diversity among the two biotypes, especially membrane and lipoproteins, most likely contribute to the differences in the pathogenesis of the two S. gallolyticus biotypes and the type of disease an infected patient eventually develops.

  4. Analysis using large-scale ringing data

    Directory of Open Access Journals (Sweden)

    Baillie, S. R.

    2004-06-01

    ]; Peach et al., 1998; DeSante et al., 2001 are generally co–ordinated by ringing centres such as those that make up the membership of EURING. In some countries volunteer census work (often called Breeding Bird Surveys is undertaken by the same organizations while in others different bodies may co–ordinate this aspect of the work. This session was concerned with the analysis of such extensive data sets and the approaches that are being developed to address the key theoretical and applied issues outlined above. The papers reflect the development of more spatially explicit approaches to analyses of data gathered at large spatial scales. They show that while the statistical tools that have been developed in recent years can be used to derive useful biological conclusions from such data, there is additional need for further developments. Future work should also consider how to best implement such analytical developments within future study designs. In his plenary paper Andy Royle (Royle, 2004 addresses this theme directly by describing a general framework for modelling spatially replicated abundance data. The approach is based on the idea that a set of spatially referenced local populations constitutes a metapopulation, within which local abundance is determined as a random process. This provides an elegant and general approach in which the metapopulation model as described above is combined with a data–generating model specific to the type of data being analysed to define a simple hierarchical model that can be analysed using conventional methods. It should be noted, however, that further software development will be needed if the approach is to be made readily available to biologists. The approach is well suited to dealing with sparse data and avoids the need for data aggregation prior to analysis. Spatial synchrony has received most attention in studies of species whose populations show cyclic fluctuations, particularly certain game birds and small mammals. However

  5. Be-Breeder - an application for analysis of genomic data in plant breeding

    OpenAIRE

    Matias,Filipe Inácio; Granato,Italo Stefanine Correa; Dequigiovanni,Gabriel; Fritsche-Neto,Roberto

    2017-01-01

    Abstract Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker) analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genome selection, genome association, and genetic diversity in a simple manner on line. ...

  6. Identification of conserved regulatory elements by comparative genome analysis

    Directory of Open Access Journals (Sweden)

    Jareborg Niclas

    2003-05-01

    Full Text Available Abstract Background For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. Results We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. Conclusions Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.

  7. EG-13GENOME-WIDE METHYLATION ANALYSIS IDENTIFIES GENOMIC DNA DEMETHYLATION DURING MALIGNANT PROGRESSION OF GLIOMAS

    Science.gov (United States)

    Saito, Kuniaki; Mukasa, Akitake; Nagae, Genta; Aihara, Koki; Otani, Ryohei; Takayanagi, Shunsaku; Omata, Mayu; Tanaka, Shota; Shibahara, Junji; Takahashi, Miwako; Momose, Toshimitsu; Shimamura, Teppei; Miyano, Satoru; Narita, Yoshitaka; Ueki, Keisuke; Nishikawa, Ryo; Nagane, Motoo; Aburatani, Hiroyuki; Saito, Nobuhito

    2014-01-01

    Low-grade gliomas often undergo malignant progression, and these transformations are a leading cause of death in patients with low-grade gliomas. However, the molecular mechanisms underlying malignant tumor progression are still not well understood. Recent evidence indicates that epigenetic deregulation is an important cause of gliomagenesis; therefore, we examined the impact of epigenetic changes during malignant progression of low-grade gliomas. Specifically, we used the Illumina Infinium Human Methylation 450K BeadChip to perform genome-wide DNA methylation analysis of 120 gliomas and four normal brains. This study sample included 25 matched-pairs of initial low-grade gliomas and recurrent tumors (temporal heterogeneity) and 20 of the 25 recurring tumors recurred as malignant progressions, and one matched-pair of newly emerging malignant lesions and pre-existing lesions (spatial heterogeneity). Analyses of methylation profiles demonstrated that most low-grade gliomas in our sample (43/51; 84%) had a CpG island methylator phenotype (G-CIMP). Remarkably, approximately 50% of secondary glioblastomas that had progressed from low-grade tumors with the G-CIMP status exhibited a characteristic partial demethylation of genomic DNA during malignant progression, but other recurrent gliomas showed no apparent change in DNA methylation pattern. Interestingly, we found that most loci that were demethylated during malignant progression were located outside of CpG islands. The information of histone modifications patterns in normal human astrocytes and embryonal stem cells also showed that the ratio of active marks at the site corresponding to DNA demethylated loci in G-CIMP-demethylated tumors was significantly lower; this finding indicated that most demethylated loci in G-CIMP-demethylated tumors were likely transcriptionally inactive. A small number of the genes that were upregulated and had demethylated CpG islands were associated with cell cycle-related pathway. In

  8. Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

    Science.gov (United States)

    Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

    2016-01-01

    3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

  9. Mokken scale analysis : Between the Guttman scale and parametric item response theory

    NARCIS (Netherlands)

    van Schuur, Wijbrandt H.

    2003-01-01

    This article introduces a model of ordinal unidimensional measurement known as Mokken scale analysis. Mokken scaling is based on principles of Item Response Theory (IRT) that originated in the Guttman scale. I compare the Mokken model with both Classical Test Theory (reliability or factor analysis)

  10. Susceptibility to Childhood Pneumonia: A Genome-Wide Analysis.

    Science.gov (United States)

    Hayden, Lystra P; Cho, Michael H; McDonald, Merry-Lynn N; Crapo, James D; Beaty, Terri H; Silverman, Edwin K; Hersh, Craig P

    2017-01-01

    Previous studies have indicated that in adult smokers, a history of childhood pneumonia is associated with reduced lung function and chronic obstructive pulmonary disease. There have been few previous investigations using genome-wide association studies to investigate genetic predisposition to pneumonia. This study aims to identify the genetic variants associated with the development of pneumonia during childhood and over the course of the lifetime. Study subjects included current and former smokers with and without chronic obstructive pulmonary disease participating in the COPDGene Study. Pneumonia was defined by subject self-report, with childhood pneumonia categorized as having the first episode at pneumonia (843 cases, 9,091 control subjects) and lifetime pneumonia (3,766 cases, 5,659 control subjects) were performed separately in non-Hispanic whites and African Americans. Non-Hispanic white and African American populations were combined in the meta-analysis. Top genetic variants from childhood pneumonia were assessed in network analysis. No single-nucleotide polymorphisms reached genome-wide significance, although we identified potential regions of interest. In the childhood pneumonia analysis, this included variants in NGR1 (P = 6.3 × 10 -8 ), PAK6 (P = 3.3 × 10 -7 ), and near MATN1 (P = 2.8 × 10 -7 ). In the lifetime pneumonia analysis, this included variants in LOC339862 (P = 8.7 × 10 -7 ), RAPGEF2 (P = 8.4 × 10 -7 ), PHACTR1 (P = 6.1 × 10 -7 ), near PRR27 (P = 4.3 × 10 -7 ), and near MCPH1 (P = 2.7 × 10 -7 ). Network analysis of the genes associated with childhood pneumonia included top networks related to development, blood vessel morphogenesis, muscle contraction, WNT signaling, DNA damage, apoptosis, inflammation, and immune response (P ≤ 0.05). We have identified genes potentially associated with the risk of pneumonia. Further research will be required to confirm these

  11. LocateP: Genome-scale subcellular-location predictor for bacterial proteins

    Directory of Open Access Journals (Sweden)

    Zhou Miaomiao

    2008-03-01

    Full Text Available Abstract Background In the past decades, various protein subcellular-location (SCL predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. Results LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms

  12. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Science.gov (United States)

    Barnes, Kayla G; Weedall, Gareth D; Ndula, Miranda; Irving, Helen; Mzihalowa, Themba; Hemingway, Janet; Wondji, Charles S

    2017-02-01

    Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  13. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Directory of Open Access Journals (Sweden)

    Kayla G Barnes

    2017-02-01

    Full Text Available Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  14. Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

    Science.gov (United States)

    Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

    2008-02-01

    The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

  15. Genomic Analysis and Comparison of Two Gonorrhea Outbreaks

    Directory of Open Access Journals (Sweden)

    Xavier Didelot

    2016-06-01

    Full Text Available Gonorrhea is a sexually transmitted disease causing growing concern, with a substantial increase in reported incidence over the past few years in the United Kingdom and rising levels of resistance to a wide range of antibiotics. Understanding its epidemiology is therefore of major biomedical importance, not only on a population scale but also at the level of direct transmission. However, the molecular typing techniques traditionally used for gonorrhea infections do not provide sufficient resolution to investigate such fine-scale patterns. Here we sequenced the genomes of 237 isolates from two local collections of isolates from Sheffield and London, each of which was resolved into a single type using traditional methods. The two data sets were selected to have different epidemiological properties: the Sheffield data were collected over 6 years from a predominantly heterosexual population, whereas the London data were gathered within half a year and strongly associated with men who have sex with men. Based on contact tracing information between individuals in Sheffield, we found that transmission is associated with a median time to most recent common ancestor of 3.4 months, with an upper bound of 8 months, which we used as a criterion to identify likely transmission links in both data sets. In London, we found that transmission happened predominantly between individuals of similar age, sexual orientation, and location and also with the same HIV serostatus, which may reflect serosorting and associated risk behaviors. Comparison of the two data sets suggests that the London epidemic involved about ten times more cases than the Sheffield outbreak.

  16. Scaling analysis in bepu licensing of LWR

    Energy Technology Data Exchange (ETDEWEB)

    D' auria, Francesco; Lanfredini, Marco; Muellner, Nikolaus [University of Pisa, Pisa (Italy)

    2012-08-15

    'Scaling' plays an important role for safety analyses in the licensing of water cooled nuclear power reactors. Accident analyses, a sub set of safety analyses, is mostly based on nuclear reactor system thermal hydraulics, and therefore based on an adequate experimental data base, and in recent licensing applications, on best estimate computer code calculations. In the field of nuclear reactor technology, only a small set of the needed experiments can be executed at a nuclear power plant; the major part of experiments, either because of economics or because of safety concerns, has to be executed at reduced scale facilities. How to address the scaling issue has been the subject of numerous investigations in the past few decades (a lot of work has been performed in the 80thies and 90thies of the last century), and is still the focus of many scientific studies. The present paper proposes a 'roadmap' to scaling. Key elements are the 'scaling-pyramid', related 'scaling bridges' and a logical path across scaling achievements (which constitute the 'scaling puzzle'). The objective is addressing the scaling issue when demonstrating the applicability of the system codes, the 'key-to-scaling', in the licensing process of a nuclear power plant. The proposed 'road map to scaling' aims at solving the 'scaling puzzle', by introducing a unified approach to the problem.

  17. Scaling analysis in bepu licensing of LWR

    International Nuclear Information System (INIS)

    D'auria, Francesco; Lanfredini, Marco; Muellner, Nikolaus

    2012-01-01

    'Scaling' plays an important role for safety analyses in the licensing of water cooled nuclear power reactors. Accident analyses, a sub set of safety analyses, is mostly based on nuclear reactor system thermal hydraulics, and therefore based on an adequate experimental data base, and in recent licensing applications, on best estimate computer code calculations. In the field of nuclear reactor technology, only a small set of the needed experiments can be executed at a nuclear power plant; the major part of experiments, either because of economics or because of safety concerns, has to be executed at reduced scale facilities. How to address the scaling issue has been the subject of numerous investigations in the past few decades (a lot of work has been performed in the 80thies and 90thies of the last century), and is still the focus of many scientific studies. The present paper proposes a 'roadmap' to scaling. Key elements are the 'scaling-pyramid', related 'scaling bridges' and a logical path across scaling achievements (which constitute the 'scaling puzzle'). The objective is addressing the scaling issue when demonstrating the applicability of the system codes, the 'key-to-scaling', in the licensing process of a nuclear power plant. The proposed 'road map to scaling' aims at solving the 'scaling puzzle', by introducing a unified approach to the problem.

  18. Genome analysis and DNA marker-based characterisation of pathogenic trypanosomes

    NARCIS (Netherlands)

    Agbo, Edwin Chukwura

    2003-01-01

    The advances in genomics technologies and genome analysis methods that offer new leads for accelerating discovery of putative targets for developing overall control tools are reviewed in Chapter 1. In Chapter 2, a PCR typing method based on restriction fragment length polymorphism analysis of the

  19. Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis.

    Science.gov (United States)

    Patil, Gunvant; Valliyodan, Babu; Deshmukh, Rupesh; Prince, Silvas; Nicander, Bjorn; Zhao, Mingzhe; Sonah, Humira; Song, Li; Lin, Li; Chaudhary, Juhi; Liu, Yang; Joshi, Trupti; Xu, Dong; Nguyen, Henry T

    2015-07-11

    SWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported. In the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6. Present investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research

  20. A protocol for large scale genomic DNA isolation for cacao genetics ...

    African Journals Online (AJOL)

    Advances in DNA technology, such as marker assisted selection, detection of quantitative trait loci and genomic selection also require the isolation of DNA from a large number of samples and the preservation of tissue samples for future use in cacao genome studies. The present study proposes a method for the ...

  1. A genome-scale RNA-interference screen identifies RRAS signaling as a pathologic feature of Huntington's disease.

    Directory of Open Access Journals (Sweden)

    John P Miller

    Full Text Available A genome-scale RNAi screen was performed in a mammalian cell-based assay to identify modifiers of mutant huntingtin toxicity. Ontology analysis of suppressor data identified processes previously implicated in Huntington's disease, including proteolysis, glutamate excitotoxicity, and mitochondrial dysfunction. In addition to established mechanisms, the screen identified multiple components of the RRAS signaling pathway as loss-of-function suppressors of mutant huntingtin toxicity in human and mouse cell models. Loss-of-function in orthologous RRAS pathway members also suppressed motor dysfunction in a Drosophila model of Huntington's disease. Abnormal activation of RRAS and a down-stream effector, RAF1, was observed in cellular models and a mouse model of Huntington's disease. We also observe co-localization of RRAS and mutant huntingtin in cells and in mouse striatum, suggesting that activation of R-Ras may occur through protein interaction. These data indicate that mutant huntingtin exerts a pathogenic effect on this pathway that can be corrected at multiple intervention points including RRAS, FNTA/B, PIN1, and PLK1. Consistent with these results, chemical inhibition of farnesyltransferase can also suppress mutant huntingtin toxicity. These data suggest that pharmacological inhibition of RRAS signaling may confer therapeutic benefit in Huntington's disease.

  2. Large-scale trends in the evolution of gene structures within 11 animal genomes.

    Directory of Open Access Journals (Sweden)

    Mark Yandell

    2006-03-01

    Full Text Available We have used the annotations of six animal genomes (Homo sapiens, Mus musculus, Ciona intestinalis, Drosophila melanogaster, Anopheles gambiae, and Caenorhabditis elegans together with the sequences of five unannotated Drosophila genomes to survey changes in protein sequence and gene structure over a variety of timescales--from the less than 5 million years since the divergence of D. simulans and D. melanogaster to the more than 500 million years that have elapsed since the Cambrian explosion. To do so, we have developed a new open-source software library called CGL (for "Comparative Genomics Library". Our results demonstrate that change in intron-exon structure is gradual, clock-like, and largely independent of coding-sequence evolution. This means that genome annotations can be used in new ways to inform, corroborate, and test conclusions drawn from comparative genomics analyses that are based upon protein and nucleotide sequence similarities.

  3. Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats.

    Science.gov (United States)

    Nazaripanah, N; Adelirad, F; Delbari, A; Sahaf, R; Abbasi-Asl, T; Ohadi, M

    2018-04-05

    While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution. Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

  4. Complete Chloroplast Genomes of Papaver rhoeas and Papaver orientale: Molecular Structures, Comparative Analysis, and Phylogenetic Analysis

    Directory of Open Access Journals (Sweden)

    Jianguo Zhou

    2018-02-01

    Full Text Available Papaver rhoeas L. and P. orientale L., which belong to the family Papaveraceae, are used as ornamental and medicinal plants. The chloroplast genome has been used for molecular markers, evolutionary biology, and barcoding identification. In this study, the complete chloroplast genome sequences of P. rhoeas and P. orientale are reported. Results show that the complete chloroplast genomes of P. rhoeas and P. orientale have typical quadripartite structures, which are comprised of circular 152,905 and 152,799-bp-long molecules, respectively. A total of 130 genes were identified in each genome, including 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Sequence divergence analysis of four species from Papaveraceae indicated that the most divergent regions are found in the non-coding spacers with minimal differences among three Papaver species. These differences include the ycf1 gene and intergenic regions, such as rpoB-trnC, trnD-trnT, petA-psbJ, psbE-petL, and ccsA-ndhD. These regions are hypervariable regions, which can be used as specific DNA barcodes. This finding suggested that the chloroplast genome could be used as a powerful tool to resolve the phylogenetic positions and relationships of Papaveraceae. These results offer valuable information for future research in the identification of Papaver species and will benefit further investigations of these species.

  5. Five Complete Chloroplast Genome Sequences from Diospyros: Genome Organization and Comparative Analysis.

    Science.gov (United States)

    Fu, Jianmin; Liu, Huimin; Hu, Jingjing; Liang, Yuqin; Liang, Jinjun; Wuyun, Tana; Tan, Xiaofeng

    2016-01-01

    Diospyros is the largest genus in Ebenaceae, comprising more than 500 species with remarkable economic value, especially Diospyros kaki Thunb., which has traditionally been an important food resource in China, Korea, and Japan. Complete chloroplast (cp) genomes from D. kaki, D. lotus L., D. oleifera Cheng., D. glaucifolia Metc., and Diospyros 'Jinzaoshi' were sequenced using Illumina sequencing technology. This is the first cp genome reported in Ebenaceae. The cp genome sequences of Diospyros ranged from 157,300 to 157,784 bp in length, presenting a typical quadripartite structure with two inverted repeats each separated by one large and one small single-copy region. For each cp genome, 134 genes were annotated, including 80 protein-coding, 31 tRNA, and 4 rRNA unique genes. In all, 179 repeats and 283 single sequence repeats were identified. Four hypervariable regions, namely, intergenic region of trnQ_rps16, trnV_ndhC, and psbD_trnT, and intron of ndhA, were identified in the Diospyros genomes. Phylogenetic analyses based on the whole cp genome, protein-coding, and intergenic and intron sequences indicated that D. oleifera is closely related to D. kaki and could be used as a model plant for future research on D. kaki; to our knowledge, this is proposed for the first time. Further, these analyses together with two large deletions (301 and 140 bp) in the cp genome of D. 'Jinzaoshi', support its placement as a new species in Diospyros. Both maximum parsimony and likelihood analyses for 19 taxa indicated the basal position of Ericales in asterids and suggested that Ebenaceae is monophyletic in Ericales.

  6. Five Complete Chloroplast Genome Sequences from Diospyros: Genome Organization and Comparative Analysis.

    Directory of Open Access Journals (Sweden)

    Jianmin Fu

    Full Text Available Diospyros is the largest genus in Ebenaceae, comprising more than 500 species with remarkable economic value, especially Diospyros kaki Thunb., which has traditionally been an important food resource in China, Korea, and Japan. Complete chloroplast (cp genomes from D. kaki, D. lotus L., D. oleifera Cheng., D. glaucifolia Metc., and Diospyros 'Jinzaoshi' were sequenced using Illumina sequencing technology. This is the first cp genome reported in Ebenaceae. The cp genome sequences of Diospyros ranged from 157,300 to 157,784 bp in length, presenting a typical quadripartite structure with two inverted repeats each separated by one large and one small single-copy region. For each cp genome, 134 genes were annotated, including 80 protein-coding, 31 tRNA, and 4 rRNA unique genes. In all, 179 repeats and 283 single sequence repeats were identified. Four hypervariable regions, namely, intergenic region of trnQ_rps16, trnV_ndhC, and psbD_trnT, and intron of ndhA, were identified in the Diospyros genomes. Phylogenetic analyses based on the whole cp genome, protein-coding, and intergenic and intron sequences indicated that D. oleifera is closely related to D. kaki and could be used as a model plant for future research on D. kaki; to our knowledge, this is proposed for the first time. Further, these analyses together with two large deletions (301 and 140 bp in the cp genome of D. 'Jinzaoshi', support its placement as a new species in Diospyros. Both maximum parsimony and likelihood analyses for 19 taxa indicated the basal position of Ericales in asterids and suggested that Ebenaceae is monophyletic in Ericales.

  7. Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

    Science.gov (United States)

    Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

    2018-03-19

    Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

  8. Analysis of the Complete Chloroplast Genome of a Medicinal Plant, Dianthus superbus var. longicalyncinus, from a Comparative Genomics Perspective.

    Science.gov (United States)

    Raman, Gurusamy; Park, SeonJoo

    2015-01-01

    Dianthus superbus var. longicalycinus is an economically important traditional Chinese medicinal plant that is also used for ornamental purposes. In this study, D. superbus was compared to its closely related family of Caryophyllaceae chloroplast (cp) genomes such as Lychnis chalcedonica and Spinacia oleracea. D. superbus had the longest large single copy (LSC) region (82,805 bp), with some variations in the inverted repeat region A (IRA)/LSC regions. The IRs underwent both expansion and constriction during evolution of the Caryophyllaceae family; however, intense variations were not identified. The pseudogene ribosomal protein subunit S19 (rps19) was identified at the IRA/LSC junction, but was not present in the cp genome of other Caryophyllaceae family members. The translation initiation factor IF-1 (infA) and ribosomal protein subunit L23 (rpl23) genes were absent from the Dianthus cp genome. When the cp genome of Dianthus was compared with 31 other angiosperm lineages, the infA gene was found to have been lost in most members of rosids, solanales of asterids and Lychnis of Caryophyllales, whereas rpl23 gene loss or pseudogization had occurred exclusively in Caryophyllales. Nevertheless, the cp genome of Dianthus and Spinacia has two introns in the proteolytic subunit of ATP-dependent protease (clpP) gene, but Lychnis has lost introns from the clpP gene. Furthermore, phylogenetic analysis of individual protein-coding genes infA and rpl23 revealed that gene loss or pseudogenization occurred independently in the cp genome of Dianthus. Molecular phylogenetic analysis also demonstrated a sister relationship between Dianthus and Lychnis based on 78 protein-coding sequences. The results presented herein will contribute to studies of the evolution, molecular biology and genetic engineering of the medicinal and ornamental plant, D. superbus var. longicalycinus.

  9. Analysis of the Complete Chloroplast Genome of a Medicinal Plant, Dianthus superbus var. longicalyncinus, from a Comparative Genomics Perspective.

    Directory of Open Access Journals (Sweden)

    Gurusamy Raman

    Full Text Available Dianthus superbus var. longicalycinus is an economically important traditional Chinese medicinal plant that is also used for ornamental purposes. In this study, D. superbus was compared to its closely related family of Caryophyllaceae chloroplast (cp genomes such as Lychnis chalcedonica and Spinacia oleracea. D. superbus had the longest large single copy (LSC region (82,805 bp, with some variations in the inverted repeat region A (IRA/LSC regions. The IRs underwent both expansion and constriction during evolution of the Caryophyllaceae family; however, intense variations were not identified. The pseudogene ribosomal protein subunit S19 (rps19 was identified at the IRA/LSC junction, but was not present in the cp genome of other Caryophyllaceae family members. The translation initiation factor IF-1 (infA and ribosomal protein subunit L23 (rpl23 genes were absent from the Dianthus cp genome. When the cp genome of Dianthus was compared with 31 other angiosperm lineages, the infA gene was found to have been lost in most members of rosids, solanales of asterids and Lychnis of Caryophyllales, whereas rpl23 gene loss or pseudogization had occurred exclusively in Caryophyllales. Nevertheless, the cp genome of Dianthus and Spinacia has two introns in the proteolytic subunit of ATP-dependent protease (clpP gene, but Lychnis has lost introns from the clpP gene. Furthermore, phylogenetic analysis of individual protein-coding genes infA and rpl23 revealed that gene loss or pseudogenization occurred independently in the cp genome of Dianthus. Molecular phylogenetic analysis also demonstrated a sister relationship between Dianthus and Lychnis based on 78 protein-coding sequences. The results presented herein will contribute to studies of the evolution, molecular biology and genetic engineering of the medicinal and ornamental plant, D. superbus var. longicalycinus.

  10. Rice-arsenate interactions in hydroponics: whole genome transcriptional analysis.

    Science.gov (United States)

    Norton, Gareth J; Lou-Hing, Daniel E; Meharg, Andrew A; Price, Adam H

    2008-01-01

    Rice (Oryza sativa) varieties that are arsenate-tolerant (Bala) and -sensitive (Azucena) were used to conduct a transcriptome analysis of the response of rice seedlings to sodium arsenate (AsV) in hydroponic solution. RNA extracted from the roots of three replicate experiments of plants grown for 1 week in phosphate-free nutrient with or without 13.3 muM AsV was used to challenge the Affymetrix (52K) GeneChip Rice Genome array. A total of 576 probe sets were significantly up-regulated at least 2-fold in both varieties, whereas 622 were down-regulated. Ontological classification is presented. As expected, a large number of transcription factors, stress proteins, and transporters demonstrated differential expression. Striking is the lack of response of classic oxidative stress-responsive genes or phytochelatin synthases/synthatases. However, the large number of responses from genes involved in glutathione synthesis, metabolism, and transport suggests that glutathione conjugation and arsenate methylation may be important biochemical responses to arsenate challenge. In this report, no attempt is made to dissect differences in the response of the tolerant and sensitive variety, but analysis in a companion article will link gene expression to the known tolerance loci available in the BalaxAzucena mapping population.

  11. Rice–arsenate interactions in hydroponics: whole genome transcriptional analysis

    Science.gov (United States)

    Norton, Gareth J.; Lou-Hing, Daniel E.; Meharg, Andrew A.; Price, Adam H.

    2008-01-01

    Rice (Oryza sativa) varieties that are arsenate-tolerant (Bala) and -sensitive (Azucena) were used to conduct a transcriptome analysis of the response of rice seedlings to sodium arsenate (AsV) in hydroponic solution. RNA extracted from the roots of three replicate experiments of plants grown for 1 week in phosphate-free nutrient with or without 13.3 μM AsV was used to challenge the Affymetrix (52K) GeneChip Rice Genome array. A total of 576 probe sets were significantly up-regulated at least 2-fold in both varieties, whereas 622 were down-regulated. Ontological classification is presented. As expected, a large number of transcription factors, stress proteins, and transporters demonstrated differential expression. Striking is the lack of response of classic oxidative stress-responsive genes or phytochelatin synthases/synthatases. However, the large number of responses from genes involved in glutathione synthesis, metabolism, and transport suggests that glutathione conjugation and arsenate methylation may be important biochemical responses to arsenate challenge. In this report, no attempt is made to dissect differences in the response of the tolerant and sensitive variety, but analysis in a companion article will link gene expression to the known tolerance loci available in the Bala×Azucena mapping population. PMID:18453530

  12. Lignin degradation: microorganisms, enzymes involved, genomes analysis and evolution.

    Science.gov (United States)

    Janusz, Grzegorz; Pawlik, Anna; Sulej, Justyna; Swiderska-Burek, Urszula; Jarosz-Wilkolazka, Anna; Paszczynski, Andrzej

    2017-11-01

    Extensive research efforts have been dedicated to describing degradation of wood, which is a complex process; hence, microorganisms have evolved different enzymatic and non-enzymatic strategies to utilize this plentiful plant material. This review describes a number of fungal and bacterial organisms which have developed both competitive and mutualistic strategies for the decomposition of wood and to thrive in different ecological niches. Through the analysis of the enzymatic machinery engaged in wood degradation, it was possible to elucidate different strategies of wood decomposition which often depend on ecological niches inhabited by given organism. Moreover, a detailed description of low molecular weight compounds is presented, which gives these organisms not only an advantage in wood degradation processes, but seems rather to be a new evolutionatory alternative to enzymatic combustion. Through analysis of genomics and secretomic data, it was possible to underline the probable importance of certain wood-degrading enzymes produced by different fungal organisms, potentially giving them advantage in their ecological niches. The paper highlights different fungal strategies of wood degradation, which possibly correlates to the number of genes coding for secretory enzymes. Furthermore, investigation of the evolution of wood-degrading organisms has been described. © FEMS 2017.

  13. Comparative genome analysis of Bacillus cereus group genomes withBacillus subtilis

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Iain; Sorokin, Alexei; Kapatral, Vinayak; Reznik, Gary; Bhattacharya, Anamitra; Mikhailova, Natalia; Burd, Henry; Joukov, Victor; Kaznadzey, Denis; Walunas, Theresa; D' Souza, Mark; Larsen, Niels; Pusch,Gordon; Liolios, Konstantinos; Grechkin, Yuri; Lapidus, Alla; Goltsman,Eugene; Chu, Lien; Fonstein, Michael; Ehrlich, S. Dusko; Overbeek, Ross; Kyrpides, Nikos; Ivanova, Natalia

    2005-09-14

    Genome features of the Bacillus cereus group genomes (representative strains of Bacillus cereus, Bacillus anthracis and Bacillus thuringiensis sub spp israelensis) were analyzed and compared with the Bacillus subtilis genome. A core set of 1,381 protein families among the four Bacillus genomes, with an additional set of 933 families common to the B. cereus group, was identified. Differences in signal transduction pathways, membrane transporters, cell surface structures, cell wall, and S-layer proteins suggesting differences in their phenotype were identified. The B. cereus group has signal transduction systems including a tyrosine kinase related to two-component system histidine kinases from B. subtilis. A model for regulation of the stress responsive sigma factor sigmaB in the B. cereus group different from the well studied regulation in B. subtilis has been proposed. Despite a high degree of chromosomal synteny among these genomes, significant differences in cell wall and spore coat proteins that contribute to the survival and adaptation in specific hosts has been identified.

  14. ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

    Science.gov (United States)

    Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

  15. Comparative genomic in situ hybridization analysis on the ...

    African Journals Online (AJOL)

    The nucleolar organizing regions (NORs), a few telomeres, most centromeric regions and numerous interstitial sites were detected. The signals in small genomes were relatively sparse and unevenly distributed along chromosomes, whereas those in large genomes were dense and basically evenly distributed.

  16. Whole-genome sequence-based analysis of thyroid function

    DEFF Research Database (Denmark)

    Taylor, Peter N.; Porcu, Eleonora; Chew, Shelby

    2015-01-01

    Normal thyroid function is essential for health, but its genetic architecture remains poorly understood. Here, for the heritable thyroid traits thyrotropin (TSH) and free thyroxine (FT4), we analyse whole-genome sequence data from the UK10K project (N = 2,287). Using additional whole-genome seque...

  17. A bibliometric analysis of global research on genome sequencing ...

    African Journals Online (AJOL)

    The results show that disease and protein related researches were the leading research focuses, and comparative genomics and evolution related research had strong potential in the near future. Key words: Genome sequencing, research trend, scientometrics, science citation index expanded (SCI-Expanded), word cluster ...

  18. Mainstreaming sex and gender analysis in public health genomics

    NARCIS (Netherlands)

    Verdonk, P.; Klinge, I.

    2012-01-01

    Background: The integration of genome-based knowledge into public health or public health genomics (PHG) aims to contribute to disease prevention, health promotion, and risk reduction associated with genetic disease susceptibility. Men and women differ, for instance, in susceptibilities for heart

  19. HyDe: a Python Package for Genome-Scale Hybridization Detection.

    Science.gov (United States)

    Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S

    2018-03-19

    The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

  20. Genome-wide association study and biological pathway analysis of the Eimeria maxima response in broilers.

    Science.gov (United States)

    Hamzić, Edin; Buitenhuis, Bart; Hérault, Frédéric; Hawken, Rachel; Abrahamsen, Mitchel S; Servin, Bertrand; Elsen, Jean-Michel; Pinard-van der Laan, Marie-Hélène; Bed'Hom, Bertrand

    2015-11-25

    Coccidiosis is the most common and costly disease in the poultry industry and is caused by protozoans of the Eimeria genus. The current control of coccidiosis, based on the use of anticoccidial drugs and vaccination, faces serious obstacles such as drug resistance and the high costs for the development of efficient vaccines, respectively. Therefore, the current control programs must be expanded with complementary approaches such as the use of genetics to improve the host response to Eimeria infections. Recently, we have performed a large-scale challenge study on Cobb500 broilers using E. maxima for which we investigated variability among animals in response to the challenge. As a follow-up to this challenge study, we performed a genome-wide association study (GWAS) to identify genomic regions underlying variability of the measured traits in the response to Eimeria maxima in broilers. Furthermore, we conducted a post-GWAS functional analysis to increase our biological understanding of the underlying response to Eimeria maxima challenge. In total, we identified 22 single nucleotide polymorphisms (SNPs) with q value Eimeria maxima in broilers. Furthermore, the post-GWAS functional analysis indicates that biological pathways and networks involved in tissue proliferation and repair along with the primary innate immune response may play the most important role during the early stage of Eimeria maxima infection in broilers.

  1. Genome-wide association study to identify common variants associated with brachial circumference: a meta-analysis of 14 cohorts.

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    Vesna Boraska

    Full Text Available Brachial circumference (BC, also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05 in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.