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

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Lee Bernett TK

2005-01-01

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

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

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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.

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...

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.

Genome scale engineering techniques for metabolic engineering.

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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.

G2S: A web-service for annotating genomic variants on 3D protein structures.

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Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-01-27

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that support programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design conception and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Global MLST of Salmonella Typhi Revisited in Post-Genomic Era: Genetic conservation, Population Structure and Comparative genomics of rare sequence types

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Kien-Pong eYap

2016-03-01

Full Text Available Typhoid fever, caused by Salmonella enterica serovar Typhi, remains an important public health burden in Southeast Asia and other endemic countries. Various genotyping methods have been applied to study the genetic variations of this human-restricted pathogen. Multilocus Sequence Typing (MLST is one of the widely accepted methods, and recently, there is a growing interest in the re-application of MLST in the post-genomic era. In this study, we provide the global MLST distribution of S. Typhi utilizing both publicly available 1,826 S. Typhi genome sequences in addition to performing conventional MLST on S. Typhi strains isolated from various endemic regions spanning over a century. Our global MLST analysis confirms the predominance of two sequence types (ST1 and ST2 co-existing in the endemic regions. Interestingly, S. Typhi strains with ST8 are currently confined within the African continent. Comparative genomic analyses of ST8 and other rare STs with genomes of ST1/ST2 revealed unique mutations in important virulence genes such as flhB, sipC and tviD that may explain the variations that differentiate between seemingly successful (widespread and unsuccessful (poor dissemination S. Typhi populations. Large scale whole-genome phylogeny demonstrated evidence of phylogeographical structuring and showed that ST8 may have diverged from the earlier ancestral population of ST1 and ST2, which later lost some of its fitness advantages, leading to poor worldwide dissemination. In response to the unprecedented increase in genomic data, this study demonstrates and highlights the utility of large-scale genome-based MLST as a quick and effective approach to narrow the scope of in-depth comparative genomic analysis and consequently provide new insights into the fine scale of pathogen evolution and population structure.

The Genome-Scale Integrated Networks in Microorganisms

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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.

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

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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

Discovery, genotyping and characterization of structural variation and novel sequence at single nucleotide resolution from de novo genome assemblies on a population scale

DEFF Research Database (Denmark)

Liu, Siyang; Huang, Shujia; Rao, Junhua

2015-01-01

present a novel approach implemented in a single software package, AsmVar, to discover, genotype and characterize different forms of structural variation and novel sequence from population-scale de novo genome assemblies up to nucleotide resolution. Application of AsmVar to several human de novo genome......) as well as large deletions. However, these approaches consistently display a substantial bias against the recovery of complex structural variants and novel sequence in individual genomes and do not provide interpretation information such as the annotation of ancestral state and formation mechanism. We...... assemblies captures a wide spectrum of structural variants and novel sequences present in the human population in high sensitivity and specificity. Our method provides a direct solution for investigating structural variants and novel sequences from de novo genome assemblies, facilitating the construction...

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

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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.

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....

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

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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

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

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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.

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

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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

A scale-free structure prior for graphical models with applications in functional genomics.

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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

The SGC beyond structural genomics: redefining the role of 3D structures by coupling genomic stratification with fragment-based discovery.

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Bradley, Anthony R; Echalier, Aude; Fairhead, Michael; Strain-Damerell, Claire; Brennan, Paul; Bullock, Alex N; Burgess-Brown, Nicola A; Carpenter, Elisabeth P; Gileadi, Opher; Marsden, Brian D; Lee, Wen Hwa; Yue, Wyatt; Bountra, Chas; von Delft, Frank

2017-11-08

The ongoing explosion in genomics data has long since outpaced the capacity of conventional biochemical methodology to verify the large number of hypotheses that emerge from the analysis of such data. In contrast, it is still a gold-standard for early phenotypic validation towards small-molecule drug discovery to use probe molecules (or tool compounds), notwithstanding the difficulty and cost of generating them. Rational structure-based approaches to ligand discovery have long promised the efficiencies needed to close this divergence; in practice, however, this promise remains largely unfulfilled, for a host of well-rehearsed reasons and despite the huge technical advances spearheaded by the structural genomics initiatives of the noughties. Therefore the current, fourth funding phase of the Structural Genomics Consortium (SGC), building on its extensive experience in structural biology of novel targets and design of protein inhibitors, seeks to redefine what it means to do structural biology for drug discovery. We developed the concept of a Target Enabling Package (TEP) that provides, through reagents, assays and data, the missing link between genetic disease linkage and the development of usefully potent compounds. There are multiple prongs to the ambition: rigorously assessing targets' genetic disease linkages through crowdsourcing to a network of collaborating experts; establishing a systematic approach to generate the protocols and data that comprise each target's TEP; developing new, X-ray-based fragment technologies for generating high quality chemical matter quickly and cheaply; and exploiting a stringently open access model to build multidisciplinary partnerships throughout academia and industry. By learning how to scale these approaches, the SGC aims to make structures finally serve genomics, as originally intended, and demonstrate how 3D structures systematically allow new modes of druggability to be discovered for whole classes of targets. © 2017 The

Simultaneous Structural Variation Discovery in Multiple Paired-End Sequenced Genomes

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Hormozdiari, Fereydoun; Hajirasouliha, Iman; McPherson, Andrew; Eichler, Evan E.; Sahinalp, S. Cenk

Next generation sequencing technologies have been decreasing the costs and increasing the world-wide capacity for sequence production at an unprecedented rate, making the initiation of large scale projects aiming to sequence almost 2000 genomes [1]. Structural variation detection promises to be one of the key diagnostic tools for cancer and other diseases with genomic origin. In this paper, we study the problem of detecting structural variation events in two or more sequenced genomes through high throughput sequencing . We propose to move from the current model of (1) detecting genomic variations in single next generation sequenced (NGS) donor genomes independently, and (2) checking whether two or more donor genomes indeed agree or disagree on the variations (in this paper we name this framework Independent Structural Variation Discovery and Merging - ISV&M), to a new model in which we detect structural variation events among multiple genomes simultaneously.

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

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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.

Fine-scale population structure and the era of next-generation sequencing.

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Henn, Brenna M; Gravel, Simon; Moreno-Estrada, Andres; Acevedo-Acevedo, Suehelay; Bustamante, Carlos D

2010-10-15

Fine-scale population structure characterizes most continents and is especially pronounced in non-cosmopolitan populations. Roughly half of the world's population remains non-cosmopolitan and even populations within cities often assort along ethnic and linguistic categories. Barriers to random mating can be ecologically extreme, such as the Sahara Desert, or cultural, such as the Indian caste system. In either case, subpopulations accumulate genetic differences if the barrier is maintained over multiple generations. Genome-wide polymorphism data, initially with only a few hundred autosomal microsatellites, have clearly established differences in allele frequency not only among continental regions, but also within continents and within countries. We review recent evidence from the analysis of genome-wide polymorphism data for genetic boundaries delineating human population structure and the main demographic and genomic processes shaping variation, and discuss the implications of population structure for the distribution and discovery of disease-causing genetic variants, in the light of the imminent availability of sequencing data for a multitude of diverse human genomes.

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.

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.

Informational laws of genome structures

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Bonnici, Vincenzo; Manca, Vincenzo

2016-06-01

In recent years, the analysis of genomes by means of strings of length k occurring in the genomes, called k-mers, has provided important insights into the basic mechanisms and design principles of genome structures. In the present study, we focus on the proper choice of the value of k for applying information theoretic concepts that express intrinsic aspects of genomes. The value k = lg2(n), where n is the genome length, is determined to be the best choice in the definition of some genomic informational indexes that are studied and computed for seventy genomes. These indexes, which are based on information entropies and on suitable comparisons with random genomes, suggest five informational laws, to which all of the considered genomes obey. Moreover, an informational genome complexity measure is proposed, which is a generalized logistic map that balances entropic and anti-entropic components of genomes and is related to their evolutionary dynamics. Finally, applications to computational synthetic biology are briefly outlined.

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

The population genomics of begomoviruses: global scale population structure and gene flow

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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

Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

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Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

2017-01-01

As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Secure web book to store structural genomics research data.

Science.gov (United States)

Manjasetty, Babu A; Höppner, Klaus; Mueller, Uwe; Heinemann, Udo

2003-01-01

Recently established collaborative structural genomics programs aim at significantly accelerating the crystal structure analysis of proteins. These large-scale projects require efficient data management systems to ensure seamless collaboration between different groups of scientists working towards the same goal. Within the Berlin-based Protein Structure Factory, the synchrotron X-ray data collection and the subsequent crystal structure analysis tasks are located at BESSY, a third-generation synchrotron source. To organize file-based communication and data transfer at the BESSY site of the Protein Structure Factory, we have developed the web-based BCLIMS, the BESSY Crystallography Laboratory Information Management System. BCLIMS is a relational data management system which is powered by MySQL as the database engine and Apache HTTP as the web server. The database interface routines are written in Python programing language. The software is freely available to academic users. Here we describe the storage, retrieval and manipulation of laboratory information, mainly pertaining to the synchrotron X-ray diffraction experiments and the subsequent protein structure analysis, using BCLIMS.

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.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

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Anjani Ragothaman

2014-01-01

Full Text Available While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

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Data Iranata

2010-05-01

Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.

Structural and functional analysis of the finished genome of the recently isolated toxic Anabaena sp. WA102.

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Brown, Nathan M; Mueller, Ryan S; Shepardson, Jonathan W; Landry, Zachary C; Morré, Jeffrey T; Maier, Claudia S; Hardy, F Joan; Dreher, Theo W

2016-06-13

Very few closed genomes of the cyanobacteria that commonly produce toxic blooms in lakes and reservoirs are available, limiting our understanding of the properties of these organisms. A new anatoxin-a-producing member of the Nostocaceae, Anabaena sp. WA102, was isolated from a freshwater lake in Washington State, USA, in 2013 and maintained in non-axenic culture. The Anabaena sp. WA102 5.7 Mbp genome assembly has been closed with long-read, single-molecule sequencing and separately a draft genome assembly has been produced with short-read sequencing technology. The closed and draft genome assemblies are compared, showing a correlation between long repeats in the genome and the many gaps in the short-read assembly. Anabaena sp. WA102 encodes anatoxin-a biosynthetic genes, as does its close relative Anabaena sp. AL93 (also introduced in this study). These strains are distinguished by differences in the genes for light-harvesting phycobilins, with Anabaena sp. AL93 possessing a phycoerythrocyanin operon. Biologically relevant structural variants in the Anabaena sp. WA102 genome were detected only by long-read sequencing: a tandem triplication of the anaBCD promoter region in the anatoxin-a synthase gene cluster (not triplicated in Anabaena sp. AL93) and a 5-kbp deletion variant present in two-thirds of the population. The genome has a large number of mobile elements (160). Strikingly, there was no synteny with the genome of its nearest fully assembled relative, Anabaena sp. 90. Structural and functional genome analyses indicate that Anabaena sp. WA102 has a flexible genome. Genome closure, which can be readily achieved with long-read sequencing, reveals large scale (e.g., gene order) and local structural features that should be considered in understanding genome evolution and function.

Elucidating the triplicated ancestral genome structure of radish based on chromosome-level comparison with the Brassica genomes.

Science.gov (United States)

Jeong, Young-Min; Kim, Namshin; Ahn, Byung Ohg; Oh, Mijin; Chung, Won-Hyong; Chung, Hee; Jeong, Seongmun; Lim, Ki-Byung; Hwang, Yoon-Jung; Kim, Goon-Bo; Baek, Seunghoon; Choi, Sang-Bong; Hyung, Dae-Jin; Lee, Seung-Won; Sohn, Seong-Han; Kwon, Soo-Jin; Jin, Mina; Seol, Young-Joo; Chae, Won Byoung; Choi, Keun Jin; Park, Beom-Seok; Yu, Hee-Ju; Mun, Jeong-Hwan

2016-07-01

This study presents a chromosome-scale draft genome sequence of radish that is assembled into nine chromosomal pseudomolecules. A comprehensive comparative genome analysis with the Brassica genomes provides genomic evidences on the evolution of the mesohexaploid radish genome. Radish (Raphanus sativus L.) is an agronomically important root vegetable crop and its origin and phylogenetic position in the tribe Brassiceae is controversial. Here we present a comprehensive analysis of the radish genome based on the chromosome sequences of R. sativus cv. WK10039. The radish genome was sequenced and assembled into 426.2 Mb spanning >98 % of the gene space, of which 344.0 Mb were integrated into nine chromosome pseudomolecules. Approximately 36 % of the genome was repetitive sequences and 46,514 protein-coding genes were predicted and annotated. Comparative mapping of the tPCK-like ancestral genome revealed that the radish genome has intermediate characteristics between the Brassica A/C and B genomes in the triplicated segments, suggesting an internal origin from the genus Brassica. The evolutionary characteristics shared between radish and other Brassica species provided genomic evidences that the current form of nine chromosomes in radish was rearranged from the chromosomes of hexaploid progenitor. Overall, this study provides a chromosome-scale draft genome sequence of radish as well as novel insight into evolution of the mesohexaploid genomes in the tribe Brassiceae.

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...

FGWAS: Functional genome wide association analysis.

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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.

Structural genomic variation in ischemic stroke

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Matarin, Mar; Simon-Sanchez, Javier; Fung, Hon-Chung; Scholz, Sonja; Gibbs, J. Raphael; Hernandez, Dena G.; Crews, Cynthia; Britton, Angela; Wavrant De Vrieze, Fabienne; Brott, Thomas G.; Brown, Robert D.; Worrall, Bradford B.; Silliman, Scott; Case, L. Douglas; Hardy, John A.; Rich, Stephen S.; Meschia, James F.; Singleton, Andrew B.

2008-01-01

Technological advances in molecular genetics allow rapid and sensitive identification of genomic copy number variants (CNVs). This, in turn, has sparked interest in the function such variation may play in disease. While a role for copy number mutations as a cause of Mendelian disorders is well established, it is unclear whether CNVs may affect risk for common complex disorders. We sought to investigate whether CNVs may modulate risk for ischemic stroke (IS) and to provide a catalog of CNVs in patients with this disorder by analyzing copy number metrics produced as a part of our previous genome-wide single-nucleotide polymorphism (SNP)-based association study of ischemic stroke in a North American white population. We examined CNVs in 263 patients with ischemic stroke (IS). Each identified CNV was compared with changes identified in 275 neurologically normal controls. Our analysis identified 247 CNVs, corresponding to 187 insertions (76%; 135 heterozygous; 25 homozygous duplications or triplications; 2 heterosomic) and 60 deletions (24%; 40 heterozygous deletions;3 homozygous deletions; 14 heterosomic deletions). Most alterations (81%) were the same as, or overlapped with, previously reported CNVs. We report here the first genome-wide analysis of CNVs in IS patients. In summary, our study did not detect any common genomic structural variation unequivocally linked to IS, although we cannot exclude that smaller CNVs or CNVs in genomic regions poorly covered by this methodology may confer risk for IS. The application of genome-wide SNP arrays now facilitates the evaluation of structural changes through the entire genome as part of a genome-wide genetic association study. PMID:18288507

Whole-Genome Analysis of a Novel Fish Reovirus (MsReV Discloses Aquareovirus Genomic Structure Relationship with Host in Saline Environments

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Zhong-Yuan Chen

2015-08-01

Full Text Available Aquareoviruses are serious pathogens of aquatic animals. Here, genome characterization and functional gene analysis of a novel aquareovirus, largemouth bass Micropterus salmoides reovirus (MsReV, was described. It comprises 11 dsRNA segments (S1–S11 covering 24,024 bp, and encodes 12 putative proteins including the inclusion forming-related protein NS87 and the fusion-associated small transmembrane (FAST protein NS22. The function of NS22 was confirmed by expression in fish cells. Subsequently, MsReV was compared with two representative aquareoviruses, saltwater fish turbot Scophthalmus maximus reovirus (SMReV and freshwater fish grass carp reovirus strain 109 (GCReV-109. MsReV NS87 and NS22 genes have the same structure and function with those of SMReV, whereas GCReV-109 is either missing the coiled-coil region in NS79 or the gene-encoding NS22. Significant similarities are also revealed among equivalent genome segments between MsReV and SMReV, but a difference is found between MsReV and GCReV-109. Furthermore, phylogenetic analysis showed that 13 aquareoviruses could be divided into freshwater and saline environments subgroups, and MsReV was closely related to SMReV in saline environments. Consequently, these viruses from hosts in saline environments have more genomic structural similarities than the viruses from hosts in freshwater. This is the first study of the relationships between aquareovirus genomic structure and their host environments.

Large scale comparative codon-pair context analysis unveils general rules that fine-tune evolution of mRNA primary structure.

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Gabriela Moura

Full Text Available BACKGROUND: Codon usage and codon-pair context are important gene primary structure features that influence mRNA decoding fidelity. In order to identify general rules that shape codon-pair context and minimize mRNA decoding error, we have carried out a large scale comparative codon-pair context analysis of 119 fully sequenced genomes. METHODOLOGIES/PRINCIPAL FINDINGS: We have developed mathematical and software tools for large scale comparative codon-pair context analysis. These methodologies unveiled general and species specific codon-pair context rules that govern evolution of mRNAs in the 3 domains of life. We show that evolution of bacterial and archeal mRNA primary structure is mainly dependent on constraints imposed by the translational machinery, while in eukaryotes DNA methylation and tri-nucleotide repeats impose strong biases on codon-pair context. CONCLUSIONS: The data highlight fundamental differences between prokaryotic and eukaryotic mRNA decoding rules, which are partially independent of codon usage.

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

Genomic hypomethylation in the human germline associates with selective structural mutability in the human genome.

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Jian Li

Full Text Available The hotspots of structural polymorphisms and structural mutability in the human genome remain to be explained mechanistically. We examine associations of structural mutability with germline DNA methylation and with non-allelic homologous recombination (NAHR mediated by low-copy repeats (LCRs. Combined evidence from four human sperm methylome maps, human genome evolution, structural polymorphisms in the human population, and previous genomic and disease studies consistently points to a strong association of germline hypomethylation and genomic instability. Specifically, methylation deserts, the ~1% fraction of the human genome with the lowest methylation in the germline, show a tenfold enrichment for structural rearrangements that occurred in the human genome since the branching of chimpanzee and are highly enriched for fast-evolving loci that regulate tissue-specific gene expression. Analysis of copy number variants (CNVs from 400 human samples identified using a custom-designed array comparative genomic hybridization (aCGH chip, combined with publicly available structural variation data, indicates that association of structural mutability with germline hypomethylation is comparable in magnitude to the association of structural mutability with LCR-mediated NAHR. Moreover, rare CNVs occurring in the genomes of individuals diagnosed with schizophrenia, bipolar disorder, and developmental delay and de novo CNVs occurring in those diagnosed with autism are significantly more concentrated within hypomethylated regions. These findings suggest a new connection between the epigenome, selective mutability, evolution, and human disease.

Using Genomics for Natural Product Structure Elucidation.

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Tietz, Jonathan I; Mitchell, Douglas A

2016-01-01

Natural products (NPs) are the most historically bountiful source of chemical matter for drug development-especially for anti-infectives. With insights gleaned from genome mining, interest in natural product discovery has been reinvigorated. An essential stage in NP discovery is structural elucidation, which sheds light not only on the chemical composition of a molecule but also its novelty, properties, and derivatization potential. The history of structure elucidation is replete with techniquebased revolutions: combustion analysis, crystallography, UV, IR, MS, and NMR have each provided game-changing advances; the latest such advance is genomics. All natural products have a genetic basis, and the ability to obtain and interpret genomic information for structure elucidation is increasingly available at low cost to non-specialists. In this review, we describe the value of genomics as a structural elucidation technique, especially from the perspective of the natural product chemist approaching an unknown metabolite. Herein we first introduce the databases and programs of interest to the natural products chemist, with an emphasis on those currently most suited for general usability. We describe strategies for linking observed natural product-linked phenotypes to their corresponding gene clusters. We then discuss techniques for extracting structural information from genes, illustrated with numerous case examples. We also provide an analysis of the biases and limitations of the field with recommendations for future development. Our overview is not only aimed at biologically-oriented researchers already at ease with bioinformatic techniques, but also, in particular, at natural product, organic, and/or medicinal chemists not previously familiar with genomic techniques.

Macroscopic High-Temperature Structural Analysis Model of Small-Scale PCHE Prototype (II)

International Nuclear Information System (INIS)

Song, Kee Nam; Lee, Heong Yeon; Hong, Sung Deok; Park, Hong Yoon

2011-01-01

The IHX (intermediate heat exchanger) of a VHTR (very high-temperature reactor) is a core component that transfers the high heat generated by the VHTR at 950 .deg. C to a hydrogen production plant. Korea Atomic Energy Research Institute manufactured a small-scale prototype of a PCHE (printed circuit heat exchanger) that was being considered as a candidate for the IHX. In this study, as a part of high-temperature structural integrity evaluation of the small-scale PCHE prototype, we carried out high-temperature structural analysis modeling and macroscopic thermal and elastic structural analysis for the small-scale PCHE prototype under small-scale gas-loop test conditions. The modeling and analysis were performed as a precedent study prior to the performance test in the small-scale gas loop. The results obtained in this study will be compared with the test results for the small-scale PCHE. Moreover, these results will be used in the design of a medium-scale PCHE prototype

Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

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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

Genomics technologies to study structural variations in the grapevine genome

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Cardone Maria Francesca

2016-01-01

Full Text Available Grapevine is one of the most important crop plants in the world. Recently there was great expansion of genomics resources about grapevine genome, thus providing increasing efforts for molecular breeding. Current cultivars display a great level of inter-specific differentiation that needs to be investigated to reach a comprehensive understanding of the genetic basis of phenotypic differences, and to find responsible genes selected by cross breeding programs. While there have been significant advances in resolving the pattern and nature of single nucleotide polymorphisms (SNPs on plant genomes, few data are available on copy number variation (CNV. Furthermore association between structural variations and phenotypes has been described in only a few cases. We combined high throughput biotechnologies and bioinformatics tools, to reveal the first inter-varietal atlas of structural variation (SV for the grapevine genome. We sequenced and compared four table grape cultivars with the Pinot noir inbred line PN40024 genome as the reference. We detected roughly 8% of the grapevine genome affected by genomic variations. Taken into account phenotypic differences existing among the studied varieties we performed comparison of SVs among them and the reference and next we performed an in-depth analysis of gene content of polymorphic regions. This allowed us to identify genes showing differences in copy number as putative functional candidates for important traits in grapevine cultivation.

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

High-throughput SHAPE analysis reveals structures in HIV-1 genomic RNA strongly conserved across distinct biological states.

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Kevin A Wilkinson

2008-04-01

Full Text Available Replication and pathogenesis of the human immunodeficiency virus (HIV is tightly linked to the structure of its RNA genome, but genome structure in infectious virions is poorly understood. We invent high-throughput SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension technology, which uses many of the same tools as DNA sequencing, to quantify RNA backbone flexibility at single-nucleotide resolution and from which robust structural information can be immediately derived. We analyze the structure of HIV-1 genomic RNA in four biologically instructive states, including the authentic viral genome inside native particles. Remarkably, given the large number of plausible local structures, the first 10% of the HIV-1 genome exists in a single, predominant conformation in all four states. We also discover that noncoding regions functioning in a regulatory role have significantly lower (p-value < 0.0001 SHAPE reactivities, and hence more structure, than do viral coding regions that function as the template for protein synthesis. By directly monitoring protein binding inside virions, we identify the RNA recognition motif for the viral nucleocapsid protein. Seven structurally homologous binding sites occur in a well-defined domain in the genome, consistent with a role in directing specific packaging of genomic RNA into nascent virions. In addition, we identify two distinct motifs that are targets for the duplex destabilizing activity of this same protein. The nucleocapsid protein destabilizes local HIV-1 RNA structure in ways likely to facilitate initial movement both of the retroviral reverse transcriptase from its tRNA primer and of the ribosome in coding regions. Each of the three nucleocapsid interaction motifs falls in a specific genome domain, indicating that local protein interactions can be organized by the long-range architecture of an RNA. High-throughput SHAPE reveals a comprehensive view of HIV-1 RNA genome structure, and further

Integration of expression data in genome-scale metabolic network reconstructions

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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.

New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes.

Science.gov (United States)

Parker, Brian J; Moltke, Ida; Roth, Adam; Washietl, Stefan; Wen, Jiayu; Kellis, Manolis; Breaker, Ronald; Pedersen, Jakob Skou

2011-11-01

Regulatory RNA structures are often members of families with multiple paralogous instances across the genome. Family members share functional and structural properties, which allow them to be studied as a whole, facilitating both bioinformatic and experimental characterization. We have developed a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein-coding regions comprising 725 individual structures, including 48 families with known structural RNA elements. Known families identified include both noncoding RNAs, e.g., miRNAs and the recently identified MALAT1/MEN β lincRNA family; and cis-regulatory structures, e.g., iron-responsive elements. We also identify tens of new families supported by strong evolutionary evidence and other statistical evidence, such as GO term enrichments. For some of these, detailed analysis has led to the formulation of specific functional hypotheses. Examples include two hypothesized auto-regulatory feedback mechanisms: one involving six long hairpins in the 3'-UTR of MAT2A, a key metabolic gene that produces the primary human methyl donor S-adenosylmethionine; the other involving a tRNA-like structure in the intron of the tRNA maturation gene POP1. We experimentally validate the predicted MAT2A structures. Finally, we identify potential new regulatory networks, including large families of short hairpins enriched in immunity-related genes, e.g., TNF, FOS, and CTLA4, which include known transcript destabilizing elements. Our findings exemplify the diversity of post-transcriptional regulation and provide a resource for further characterization of new regulatory mechanisms and families of noncoding RNAs.

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

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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.

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.

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.

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.

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

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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.

Metabolite coupling in genome-scale metabolic networks

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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

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

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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.

SELECTION OF SCALE OF PICTURE OF STRUCTURE FOR ITS MULTIFRACTAL ANALYSIS

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VOLCHUK V. N.

2015-11-01

Full Text Available Problem statement. Each scale level detectesthe new features of the structure of the material describing of it quality. For example, features of the grain structure are revealed in different kind of steel on microstruc ture level, and its parameters greatly influences on the strength properties of the metal. Thus, to select the scale of representation of a fractal object, for instance the elements of structure of roll iron or steel is necessary to determine the interval (1, where observed its self-similarity, and on this interval should be selected the scale, the use of which will allow him to choose adequate fractal dimension. For optimal scale structure of repose is taken one in which at least two adjacent points of the series (2, the fractal dimension is minimal differences between them. This is explained by the fact that this is best observed property of self-similarity structure. An example of the selection of the scale representation of the structure of cast iron rolls execution of SPHN (a and execution SSHN (b is shown on interval of increases in the range of x 100 to x1000 with a predetermined pitch Δl = 100. The implementation of this phase of research allowed to determine experimentally the optimal scale of representation of structure of iron roll with increasing x 200 for multifractal analysis of its elements: inclusion of the plate and nodular graphit, carbides. Purpose To determine the optimal scale structure representation for iron roll multifractal analysis of its elements: inclusion of the plate and nodular carbides. Conclusion. It was found that the fractal dimension of the structural elements of the test ranged from experimental error 5÷7%, which testifies to the universality of this assessment, and therefore reliability and economic benefits, in terms of the equipping of laboratories expensive metallurgical microscopes with higher resolution.

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

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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

Visualization of RNA structure models within the Integrative Genomics Viewer.

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Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

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

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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.

Functional Coverage of the Human Genome by Existing Structures, Structural Genomics Targets, and Homology Models.

Directory of Open Access Journals (Sweden)

2005-08-01

Full Text Available The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB, target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB, it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.

Core genome conservation of Staphylococcus haemolyticus limits sequence based population structure analysis.

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Cavanagh, Jorunn Pauline; Klingenberg, Claus; Hanssen, Anne-Merethe; Fredheim, Elizabeth Aarag; Francois, Patrice; Schrenzel, Jacques; Flægstad, Trond; Sollid, Johanna Ericson

2012-06-01

The notoriously multi-resistant Staphylococcus haemolyticus is an emerging pathogen causing serious infections in immunocompromised patients. Defining the population structure is important to detect outbreaks and spread of antimicrobial resistant clones. Currently, the standard typing technique is pulsed-field gel electrophoresis (PFGE). In this study we describe novel molecular typing schemes for S. haemolyticus using multi locus sequence typing (MLST) and multi locus variable number of tandem repeats (VNTR) analysis. Seven housekeeping genes (MLST) and five VNTR loci (MLVF) were selected for the novel typing schemes. A panel of 45 human and veterinary S. haemolyticus isolates was investigated. The collection had diverse PFGE patterns (38 PFGE types) and was sampled over a 20 year-period from eight countries. MLST resolved 17 sequence types (Simpsons index of diversity [SID]=0.877) and MLVF resolved 14 repeat types (SID=0.831). We found a low sequence diversity. Phylogenetic analysis clustered the isolates in three (MLST) and one (MLVF) clonal complexes, respectively. Taken together, neither the MLST nor the MLVF scheme was suitable to resolve the population structure of this S. haemolyticus collection. Future MLVF and MLST schemes will benefit from addition of more variable core genome sequences identified by comparing different fully sequenced S. haemolyticus genomes. Copyright © 2012 Elsevier B.V. All rights reserved.

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

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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

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

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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

New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes

DEFF Research Database (Denmark)

Parker, Brian John; Moltke, Ida; Roth, Adam

2011-01-01

a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein...

Producing genome structure populations with the dynamic and automated PGS software.

Science.gov (United States)

Hua, Nan; Tjong, Harianto; Shin, Hanjun; Gong, Ke; Zhou, Xianghong Jasmine; Alber, Frank

2018-05-01

Chromosome conformation capture technologies such as Hi-C are widely used to investigate the spatial organization of genomes. Because genome structures can vary considerably between individual cells of a population, interpreting ensemble-averaged Hi-C data can be challenging, in particular for long-range and interchromosomal interactions. We pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome's organization in space and time. We provide a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix, along with information about genome segmentation, and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and provides tools to extract and analyze the 3D coordinates of specific domains. Basic Linux command-line knowledge is sufficient for using this software. A typical running time of the pipeline is ∼3 d with 300 cores on a computer cluster to generate a population of 1,000 diploid genome structures at topological-associated domain (TAD)-level resolution.

Population structure analysis using rare and common functional variants

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Ding Lili

2011-11-01

Full Text Available Abstract Next-generation sequencing technologies now make it possible to genotype and measure hundreds of thousands of rare genetic variations in individuals across the genome. Characterization of high-density genetic variation facilitates control of population genetic structure on a finer scale before large-scale genotyping in disease genetics studies. Population structure is a well-known, prevalent, and important factor in common variant genetic studies, but its relevance in rare variants is unclear. We perform an extensive population structure analysis using common and rare functional variants from the Genetic Analysis Workshop 17 mini-exome sequence. The analysis based on common functional variants required 388 principal components to account for 90% of the variation in population structure. However, an analysis based on rare variants required 532 significant principal components to account for similar levels of variation. Using rare variants, we detected fine-scale substructure beyond the population structure identified using common functional variants. Our results show that the level of population structure embedded in rare variant data is different from the level embedded in common variant data and that correcting for population structure is only as good as the level one wishes to correct.

In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features.

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Ding, Yiliang; Tang, Yin; Kwok, Chun Kit; Zhang, Yu; Bevilacqua, Philip C; Assmann, Sarah M

2014-01-30

RNA structure has critical roles in processes ranging from ligand sensing to the regulation of translation, polyadenylation and splicing. However, a lack of genome-wide in vivo RNA structural data has limited our understanding of how RNA structure regulates gene expression in living cells. Here we present a high-throughput, genome-wide in vivo RNA structure probing method, structure-seq, in which dimethyl sulphate methylation of unprotected adenines and cytosines is identified by next-generation sequencing. Application of this method to Arabidopsis thaliana seedlings yielded the first in vivo genome-wide RNA structure map at nucleotide resolution for any organism, with quantitative structural information across more than 10,000 transcripts. Our analysis reveals a three-nucleotide periodic repeat pattern in the structure of coding regions, as well as a less-structured region immediately upstream of the start codon, and shows that these features are strongly correlated with translation efficiency. We also find patterns of strong and weak secondary structure at sites of alternative polyadenylation, as well as strong secondary structure at 5' splice sites that correlates with unspliced events. Notably, in vivo structures of messenger RNAs annotated for stress responses are poorly predicted in silico, whereas mRNA structures of genes related to cell function maintenance are well predicted. Global comparison of several structural features between these two categories shows that the mRNAs associated with stress responses tend to have more single-strandedness, longer maximal loop length and higher free energy per nucleotide, features that may allow these RNAs to undergo conformational changes in response to environmental conditions. Structure-seq allows the RNA structurome and its biological roles to be interrogated on a genome-wide scale and should be applicable to any organism.

Genome-wide identification of structural variants in genes encoding drug targets

DEFF Research Database (Denmark)

Rasmussen, Henrik Berg; Dahmcke, Christina Mackeprang

2012-01-01

The objective of the present study was to identify structural variants of drug target-encoding genes on a genome-wide scale. We also aimed at identifying drugs that are potentially amenable for individualization of treatments based on knowledge about structural variation in the genes encoding...

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

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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.

Cloning, production, and purification of proteins for a medium-scale structural genomics project.

Science.gov (United States)

Quevillon-Cheruel, Sophie; Collinet, Bruno; Trésaugues, Lionel; Minard, Philippe; Henckes, Gilles; Aufrère, Robert; Blondeau, Karine; Zhou, Cong-Zhao; Liger, Dominique; Bettache, Nabila; Poupon, Anne; Aboulfath, Ilham; Leulliot, Nicolas; Janin, Joël; van Tilbeurgh, Herman

2007-01-01

The South-Paris Yeast Structural Genomics Pilot Project (http://www.genomics.eu.org) aims at systematically expressing, purifying, and determining the three-dimensional structures of Saccharomyces cerevisiae proteins. We have already cloned 240 yeast open reading frames in the Escherichia coli pET system. Eighty-two percent of the targets can be expressed in E. coli, and 61% yield soluble protein. We have currently purified 58 proteins. Twelve X-ray structures have been solved, six are in progress, and six other proteins gave crystals. In this chapter, we present the general experimental flowchart applied for this project. One of the main difficulties encountered in this pilot project was the low solubility of a great number of target proteins. We have developed parallel strategies to recover these proteins from inclusion bodies, including refolding, coexpression with chaperones, and an in vitro expression system. A limited proteolysis protocol, developed to localize flexible regions in proteins that could hinder crystallization, is also described.

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

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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

High throughput platforms for structural genomics of integral membrane proteins.

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Mancia, Filippo; Love, James

2011-08-01

Structural genomics approaches on integral membrane proteins have been postulated for over a decade, yet specific efforts are lagging years behind their soluble counterparts. Indeed, high throughput methodologies for production and characterization of prokaryotic integral membrane proteins are only now emerging, while large-scale efforts for eukaryotic ones are still in their infancy. Presented here is a review of recent literature on actively ongoing structural genomics of membrane protein initiatives, with a focus on those aimed at implementing interesting techniques aimed at increasing our rate of success for this class of macromolecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

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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.

Scaling structure loads for SMA

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Won; Song, Jeong Guk; Jeon, Sang Ho; Lim, Hak Kyu; Lee, Kwang Nam [KEPCO ENC, Yongin (Korea, Republic of)

2012-10-15

When the Seismic Margin Analysis(SMA) is conducted, the new structural load generation with Seismic Margin Earthquake(SME) is the time consuming work. For the convenience, EPRI NP 6041 suggests the scaling of the structure load. The report recommend that the fixed base(rock foundation) structure designed using either constant modal damping or modal damping ratios developed for a single material damping. For these cases, the SME loads can easily and accurately be calculated by scaling the spectral accelerations of the individual modes for the new SME response spectra. EPRI NP 6041 provides two simple methodologies for the scaling structure seismic loads which are the dominant frequency scaling methodology and the mode by mode scaling methodology. Scaling of the existing analysis to develop SME loads is much easier and more efficient than performing a new analysis. This paper is intended to compare the calculating results of two different methodologies.

Scaling structure loads for SMA

International Nuclear Information System (INIS)

Lee, Dong Won; Song, Jeong Guk; Jeon, Sang Ho; Lim, Hak Kyu; Lee, Kwang Nam

2012-01-01

When the Seismic Margin Analysis(SMA) is conducted, the new structural load generation with Seismic Margin Earthquake(SME) is the time consuming work. For the convenience, EPRI NP 6041 suggests the scaling of the structure load. The report recommend that the fixed base(rock foundation) structure designed using either constant modal damping or modal damping ratios developed for a single material damping. For these cases, the SME loads can easily and accurately be calculated by scaling the spectral accelerations of the individual modes for the new SME response spectra. EPRI NP 6041 provides two simple methodologies for the scaling structure seismic loads which are the dominant frequency scaling methodology and the mode by mode scaling methodology. Scaling of the existing analysis to develop SME loads is much easier and more efficient than performing a new analysis. This paper is intended to compare the calculating results of two different methodologies

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...

Complete Chloroplast Genomes of Papaver rhoeas and Papaver orientale: Molecular Structures, Comparative Analysis, and Phylogenetic Analysis

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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.

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.

Chloroplast genomes of Arabidopsis halleri ssp. gemmifera and Arabidopsis lyrata ssp. petraea: Structures and comparative analysis.

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Asaf, Sajjad; Khan, Abdul Latif; Khan, Muhammad Aaqil; Waqas, Muhammad; Kang, Sang-Mo; Yun, Byung-Wook; Lee, In-Jung

2017-08-08

We investigated the complete chloroplast (cp) genomes of non-model Arabidopsis halleri ssp. gemmifera and Arabidopsis lyrata ssp. petraea using Illumina paired-end sequencing to understand their genetic organization and structure. Detailed bioinformatics analysis revealed genome sizes of both subspecies ranging between 154.4~154.5 kbp, with a large single-copy region (84,197~84,158 bp), a small single-copy region (17,738~17,813 bp) and pair of inverted repeats (IRa/IRb; 26,264~26,259 bp). Both cp genomes encode 130 genes, including 85 protein-coding genes, eight ribosomal RNA genes and 37 transfer RNA genes. Whole cp genome comparison of A. halleri ssp. gemmifera and A. lyrata ssp. petraea, along with ten other Arabidopsis species, showed an overall high degree of sequence similarity, with divergence among some intergenic spacers. The location and distribution of repeat sequences were determined, and sequence divergences of shared genes were calculated among related species. Comparative phylogenetic analysis of the entire genomic data set and 70 shared genes between both cp genomes confirmed the previous phylogeny and generated phylogenetic trees with the same topologies. The sister species of A. halleri ssp. gemmifera is A. umezawana, whereas the closest relative of A. lyrata spp. petraea is A. arenicola.

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

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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.

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

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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

Chromatin structure and evolution in the human genome

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Dunlop Malcolm G

2007-05-01

Full Text Available Abstract Background Evolutionary rates are not constant across the human genome but genes in close proximity have been shown to experience similar levels of divergence and selection. The higher-order organisation of chromosomes has often been invoked to explain such phenomena but previously there has been insufficient data on chromosome structure to investigate this rigorously. Using the results of a recent genome-wide analysis of open and closed human chromatin structures we have investigated the global association between divergence, selection and chromatin structure for the first time. Results In this study we have shown that, paradoxically, synonymous site divergence (dS at non-CpG sites is highest in regions of open chromatin, primarily as a result of an increased number of transitions, while the rates of other traditional measures of mutation (intergenic, intronic and ancient repeat divergence as well as SNP density are highest in closed regions of the genome. Analysis of human-chimpanzee divergence across intron-exon boundaries indicates that although genes in relatively open chromatin generally display little selection at their synonymous sites, those in closed regions show markedly lower divergence at their fourfold degenerate sites than in neighbouring introns and intergenic regions. Exclusion of known Exonic Splice Enhancer hexamers has little affect on the divergence observed at fourfold degenerate sites across chromatin categories; however, we show that closed chromatin is enriched with certain classes of ncRNA genes whose RNA secondary structure may be particularly important. Conclusion We conclude that, overall, non-CpG mutation rates are lowest in open regions of the genome and that regions of the genome with a closed chromatin structure have the highest background mutation rate. This might reflect lower rates of DNA damage or enhanced DNA repair processes in regions of open chromatin. Our results also indicate that dS is a poor

From structure prediction to genomic screens for novel non-coding RNAs.

Science.gov (United States)

Gorodkin, Jan; Hofacker, Ivo L

2011-08-01

Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

GWAMA: software for genome-wide association meta-analysis

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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.

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

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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.

Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

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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.

Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

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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.

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.

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

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

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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

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...

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.

From structure prediction to genomic screens for novel non-coding RNAs.

Directory of Open Access Journals (Sweden)

Jan Gorodkin

2011-08-01

Full Text Available Non-coding RNAs (ncRNAs are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs. A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

Genome-wide analysis of the expansin gene superfamily reveals grapevine-specific structural and functional characteristics.

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Silvia Dal Santo

Full Text Available BACKGROUND: Expansins are proteins that loosen plant cell walls in a pH-dependent manner, probably by increasing the relative movement among polymers thus causing irreversible expansion. The expansin superfamily (EXP comprises four distinct families: expansin A (EXPA, expansin B (EXPB, expansin-like A (EXLA and expansin-like B (EXLB. There is experimental evidence that EXPA and EXPB proteins are required for cell expansion and developmental processes involving cell wall modification, whereas the exact functions of EXLA and EXLB remain unclear. The complete grapevine (Vitis vinifera genome sequence has allowed the characterization of many gene families, but an exhaustive genome-wide analysis of expansin gene expression has not been attempted thus far. METHODOLOGY/PRINCIPAL FINDINGS: We identified 29 EXP superfamily genes in the grapevine genome, representing all four EXP families. Members of the same EXP family shared the same exon-intron structure, and phylogenetic analysis confirmed a closer relationship between EXP genes from woody species, i.e. grapevine and poplar (Populus trichocarpa, compared to those from Arabidopsis thaliana and rice (Oryza sativa. We also identified grapevine-specific duplication events involving the EXLB family. Global gene expression analysis confirmed a strong correlation among EXP genes expressed in mature and green/vegetative samples, respectively, as reported for other gene families in the recently-published grapevine gene expression atlas. We also observed the specific co-expression of EXLB genes in woody organs, and the involvement of certain grapevine EXP genes in berry development and post-harvest withering. CONCLUSION: Our comprehensive analysis of the grapevine EXP superfamily confirmed and extended current knowledge about the structural and functional characteristics of this gene family, and also identified properties that are currently unique to grapevine expansin genes. Our data provide a model for the

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....

Gene Composer in a structural genomics environment

International Nuclear Information System (INIS)

Lorimer, Don; Raymond, Amy; Mixon, Mark; Burgin, Alex; Staker, Bart; Stewart, Lance

2011-01-01

For structural biology applications, protein-construct engineering is guided by comparative sequence analysis and structural information, which allow the researcher to better define domain boundaries for terminal deletions and nonconserved regions for surface mutants. A database software application called Gene Composer has been developed to facilitate construct design. The structural genomics effort at the Seattle Structural Genomics Center for Infectious Disease (SSGCID) requires the manipulation of large numbers of amino-acid sequences and the underlying DNA sequences which are to be cloned into expression vectors. To improve efficiency in high-throughput protein structure determination, a database software package, Gene Composer, has been developed which facilitates the information-rich design of protein constructs and their underlying gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bioinformatics steps used in modern structure-guided protein engineering and synthetic gene engineering. An example of the structure determination of H1N1 RNA-dependent RNA polymerase PB2 subunit is given

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

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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.

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.

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.

Cross-study analysis of genomic data defines the ciliate multigenic epiplasmin family: strategies for functional analysis in Paramecium tetraurelia

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Ravet Viviane

2009-06-01

Full Text Available Abstract Background The sub-membranous skeleton of the ciliate Paramecium, the epiplasm, is composed of hundreds of epiplasmic scales centered on basal bodies, and presents a complex set of proteins, epiplasmins, which belong to a multigenic family. The repeated duplications observed in the P. tetraurelia genome present an interesting model of the organization and evolution of a multigenic family within a single cell. Results To study this multigenic family, we used phylogenetic, structural, and analytical transcriptional approaches. The phylogenetic method defines 5 groups of epiplasmins in the multigenic family. A refined analysis by Hydrophobic Cluster Analysis (HCA identifies structural characteristics of 51 epiplasmins, defining five separate groups, and three classes. Depending on the sequential arrangement of their structural domains, the epiplasmins are defined as symmetric, asymmetric or atypical. The EST data aid in this classification, in the identification of putative regulating sequences such as TATA or CAAT boxes. When specific RNAi experiments were conducted using sequences from either symmetric or asymmetric classes, phenotypes were drastic. Local effects show either disrupted or ill-shaped epiplasmic scales. In either case, this results in aborted cell division. Using structural features, we show that 4 epiplasmins are also present in another ciliate, Tetrahymena thermophila. Their affiliation with the distinctive structural groups of Paramecium epiplasmins demonstrates an interspecific multigenic family. Conclusion The epiplasmin multigenic family illustrates the history of genomic duplication in Paramecium. This study provides a framework which can guide functional analysis of epiplasmins, the major components of the membrane skeleton in ciliates. We show that this set of proteins handles an important developmental information in Paramecium since maintenance of epiplasm organization is crucial for cell morphogenesis.

From genomes to in silico cells via metabolic networks

DEFF Research Database (Denmark)

Borodina, Irina; Nielsen, Jens

2005-01-01

Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

Exploratory analysis of genomic segmentations with Segtools

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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.

Genome-Wide Analysis of Transposon and Retroviral Insertions Reveals Preferential Integrations in Regions of DNA Flexibility.

Science.gov (United States)

Vrljicak, Pavle; Tao, Shijie; Varshney, Gaurav K; Quach, Helen Ngoc Bao; Joshi, Adita; LaFave, Matthew C; Burgess, Shawn M; Sampath, Karuna

2016-04-07

DNA transposons and retroviruses are important transgenic tools for genome engineering. An important consideration affecting the choice of transgenic vector is their insertion site preferences. Previous large-scale analyses of Ds transposon integration sites in plants were done on the basis of reporter gene expression or germ-line transmission, making it difficult to discern vertebrate integration preferences. Here, we compare over 1300 Ds transposon integration sites in zebrafish with Tol2 transposon and retroviral integration sites. Genome-wide analysis shows that Ds integration sites in the presence or absence of marker selection are remarkably similar and distributed throughout the genome. No strict motif was found, but a preference for structural features in the target DNA associated with DNA flexibility (Twist, Tilt, Rise, Roll, Shift, and Slide) was observed. Remarkably, this feature is also found in transposon and retroviral integrations in maize and mouse cells. Our findings show that structural features influence the integration of heterologous DNA in genomes, and have implications for targeted genome engineering. Copyright © 2016 Vrljicak et al.

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...

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.

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.

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

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.

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...

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...

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.

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.

2004 Structural, Function and Evolutionary Genomics

Energy Technology Data Exchange (ETDEWEB)

Douglas L. Brutlag Nancy Ryan Gray

2005-03-23

This Gordon conference will cover the areas of structural, functional and evolutionary genomics. It will take a systematic approach to genomics, examining the evolution of proteins, protein functional sites, protein-protein interactions, regulatory networks, and metabolic networks. Emphasis will be placed on what we can learn from comparative genomics and entire genomes and proteomes.

Inference of functional properties from large-scale analysis of enzyme superfamilies.

Science.gov (United States)

Brown, Shoshana D; Babbitt, Patricia C

2012-01-02

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

Science.gov (United States)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-04-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

Science.gov (United States)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-06-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

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

Directory of Open Access Journals (Sweden)

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

Practical guidelines to select and scale earthquake records for nonlinear response history analysis of structures

Science.gov (United States)

Kalkan, Erol; Chopra, Anil K.

2010-01-01

Earthquake engineering practice is increasingly using nonlinear response history analysis (RHA) to demonstrate performance of structures. This rigorous method of analysis requires selection and scaling of ground motions appropriate to design hazard levels. Presented herein is a modal-pushover-based scaling (MPS) method to scale ground motions for use in nonlinear RHA of buildings and bridges. In the MPS method, the ground motions are scaled to match (to a specified tolerance) a target value of the inelastic deformation of the first-'mode' inelastic single-degree-of-freedom (SDF) system whose properties are determined by first-'mode' pushover analysis. Appropriate for first-?mode? dominated structures, this approach is extended for structures with significant contributions of higher modes by considering elastic deformation of second-'mode' SDF system in selecting a subset of the scaled ground motions. Based on results presented for two bridges, covering single- and multi-span 'ordinary standard' bridge types, and six buildings, covering low-, mid-, and tall building types in California, the accuracy and efficiency of the MPS procedure are established and its superiority over the ASCE/SEI 7-05 scaling procedure is demonstrated.

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

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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

Considerations in the identification of functional RNA structural elements in genomic alignments

Directory of Open Access Journals (Sweden)

Blencowe Benjamin J

2007-01-01

Full Text Available Abstract Background Accurate identification of novel, functional noncoding (nc RNA features in genome sequence has proven more difficult than for exons. Current algorithms identify and score potential RNA secondary structures on the basis of thermodynamic stability, conservation, and/or covariance in sequence alignments. Neither the algorithms nor the information gained from the individual inputs have been independently assessed. Furthermore, due to issues in modelling background signal, it has been difficult to gauge the precision of these algorithms on a genomic scale, in which even a seemingly small false-positive rate can result in a vast excess of false discoveries. Results We developed a shuffling algorithm, shuffle-pair.pl, that simultaneously preserves dinucleotide frequency, gaps, and local conservation in pairwise sequence alignments. We used shuffle-pair.pl to assess precision and recall of six ncRNA search tools (MSARI, QRNA, ddbRNA, RNAz, Evofold, and several variants of simple thermodynamic stability on a test set of 3046 alignments of known ncRNAs. Relative to mononucleotide shuffling, preservation of dinucleotide content in shuffling the alignments resulted in a drastic increase in estimated false-positive detection rates for ncRNA elements, precluding evaluation of higher order alignments, which cannot not be adequately shuffled maintaining both dinucleotides and alignment structure. On pairwise alignments, none of the covariance-based tools performed markedly better than thermodynamic scoring alone. Although the high false-positive rates call into question the veracity of any individual predicted secondary structural element in our analysis, we nevertheless identified intriguing global trends in human genome alignments. The distribution of ncRNA prediction scores in 75-base windows overlapping UTRs, introns, and intergenic regions analyzed using both thermodynamic stability and EvoFold (which has no thermodynamic component was

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...

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

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...

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.

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.

Large scale identification and categorization of protein sequences using structured logistic regression.

Directory of Open Access Journals (Sweden)

Bjørn P Pedersen

Full Text Available BACKGROUND: Structured Logistic Regression (SLR is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well-suited for this task. The classification of P-type ATPases, a large family of ATP-driven membrane pumps transporting essential cations, was selected as a test-case that would generate important biological information as well as provide a proof-of-concept for the application of SLR to a large scale bioinformatics problem. RESULTS: Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known sequences, we analysed 9.3 million sequences in the UniProtKB and attempted to classify a large number of P-type ATPases. To examine the distribution of pumps on organisms, we also applied SLR to 1,123 complete genomes from the Entrez genome database. Finally, we analysed the predicted membrane topology of the identified P-type ATPases. CONCLUSIONS: Using the SLR-based classification tool we are able to run a large scale study of P-type ATPases. This study provides proof-of-concept for the application of SLR to a bioinformatics problem and the analysis of P-type ATPases pinpoints new and interesting targets for further biochemical characterization and structural analysis.

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

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.

Inference of Functional Properties from Large-scale Analysis of Enzyme Superfamilies*

Science.gov (United States)

Brown, Shoshana D.; Babbitt, Patricia C.

2012-01-01

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies. PMID:22069325

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.

SL1 revisited: functional analysis of the structure and conformation of HIV-1 genome RNA.

Science.gov (United States)

Sakuragi, Sayuri; Yokoyama, Masaru; Shioda, Tatsuo; Sato, Hironori; Sakuragi, Jun-Ichi

2016-11-11

The dimer initiation site/dimer linkage sequence (DIS/DLS) region of HIV is located on the 5' end of the viral genome and suggested to form complex secondary/tertiary structures. Within this structure, stem-loop 1 (SL1) is believed to be most important and an essential key to dimerization, since the sequence and predicted secondary structure of SL1 are highly stable and conserved among various virus subtypes. In particular, a six-base palindromic sequence is always present at the hairpin loop of SL1 and the formation of kissing-loop structure at this position between the two strands of genomic RNA is suggested to trigger dimerization. Although the higher-order structure model of SL1 is well accepted and perhaps even undoubted lately, there could be stillroom for consideration to depict the functional SL1 structure while in vivo (in virion or cell). In this study, we performed several analyses to identify the nucleotides and/or basepairing within SL1 which are necessary for HIV-1 genome dimerization, encapsidation, recombination and infectivity. We unexpectedly found that some nucleotides that are believed to contribute the formation of the stem do not impact dimerization or infectivity. On the other hand, we found that one G-C basepair involved in stem formation may serve as an alternative dimer interactive site. We also report on our further investigation of the roles of the palindromic sequences on viral replication. Collectively, we aim to assemble a more-comprehensive functional map of SL1 on the HIV-1 viral life cycle. We discovered several possibilities for a novel structure of SL1 in HIV-1 DLS. The newly proposed structure model suggested that the hairpin loop of SL1 appeared larger, and genome dimerization process might consist of more complicated mechanism than previously understood. Further investigations would be still required to fully understand the genome packaging and dimerization of HIV.

Genomic Diversity and Evolution of the Lyssaviruses

Science.gov (United States)

Delmas, Olivier; Holmes, Edward C.; Talbi, Chiraz; Larrous, Florence; Dacheux, Laurent; Bouchier, Christiane; Bourhy, Hervé

2008-01-01

Lyssaviruses are RNA viruses with single-strand, negative-sense genomes responsible for rabies-like diseases in mammals. To date, genomic and evolutionary studies have most often utilized partial genome sequences, particularly of the nucleoprotein and glycoprotein genes, with little consideration of genome-scale evolution. Herein, we report the first genomic and evolutionary analysis using complete genome sequences of all recognised lyssavirus genotypes, including 14 new complete genomes of field isolates from 6 genotypes and one genotype that is completely sequenced for the first time. In doing so we significantly increase the extent of genome sequence data available for these important viruses. Our analysis of these genome sequence data reveals that all lyssaviruses have the same genomic organization. A phylogenetic analysis reveals strong geographical structuring, with the greatest genetic diversity in Africa, and an independent origin for the two known genotypes that infect European bats. We also suggest that multiple genotypes may exist within the diversity of viruses currently classified as ‘Lagos Bat’. In sum, we show that rigorous phylogenetic techniques based on full length genome sequence provide the best discriminatory power for genotype classification within the lyssaviruses. PMID:18446239

Genomic diversity and evolution of the lyssaviruses.

Directory of Open Access Journals (Sweden)

Olivier Delmas

2008-04-01

Full Text Available Lyssaviruses are RNA viruses with single-strand, negative-sense genomes responsible for rabies-like diseases in mammals. To date, genomic and evolutionary studies have most often utilized partial genome sequences, particularly of the nucleoprotein and glycoprotein genes, with little consideration of genome-scale evolution. Herein, we report the first genomic and evolutionary analysis using complete genome sequences of all recognised lyssavirus genotypes, including 14 new complete genomes of field isolates from 6 genotypes and one genotype that is completely sequenced for the first time. In doing so we significantly increase the extent of genome sequence data available for these important viruses. Our analysis of these genome sequence data reveals that all lyssaviruses have the same genomic organization. A phylogenetic analysis reveals strong geographical structuring, with the greatest genetic diversity in Africa, and an independent origin for the two known genotypes that infect European bats. We also suggest that multiple genotypes may exist within the diversity of viruses currently classified as 'Lagos Bat'. In sum, we show that rigorous phylogenetic techniques based on full length genome sequence provide the best discriminatory power for genotype classification within the lyssaviruses.

Whole genome PCR scanning reveals the syntenic genome structure of toxigenic Vibrio cholerae strains in the O1/O139 population.

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Bo Pang

Full Text Available Vibrio cholerae is commonly found in estuarine water systems. Toxigenic O1 and O139 V. cholerae strains have caused cholera epidemics and pandemics, whereas the nontoxigenic strains within these serogroups only occasionally lead to disease. To understand the differences in the genome and clonality between the toxigenic and nontoxigenic strains of V. cholerae serogroups O1 and O139, we employed a whole genome PCR scanning (WGPScanning method, an rrn operon-mediated fragment rearrangement analysis and comparative genomic hybridization (CGH to analyze the genome structure of different strains. WGPScanning in conjunction with CGH revealed that the genomic contents of the toxigenic strains were conservative, except for a few indels located mainly in mobile elements. Minor nucleotide variation in orthologous genes appeared to be the major difference between the toxigenic strains. rrn operon-mediated rearrangements were infrequent in El Tor toxigenic strains tested using I-CeuI digested pulsed-field gel electrophoresis (PFGE analysis and PCR analysis based on flanking sequence of rrn operons. Using these methods, we found that the genomic structures of toxigenic El Tor and O139 strains were syntenic. The nontoxigenic strains exhibited more extensive sequence variations, but toxin coregulated pilus positive (TCP+ strains had a similar structure. TCP+ nontoxigenic strains could be subdivided into multiple lineages according to the TCP type, suggesting the existence of complex intermediates in the evolution of toxigenic strains. The data indicate that toxigenic O1 El Tor and O139 strains were derived from a single lineage of intermediates from complex clones in the environment. The nontoxigenic strains with non-El Tor type TCP may yet evolve into new epidemic clones after attaining toxigenic attributes.

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

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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.

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

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.

Systematic determination of the mosaic structure of bacterial genomes: species backbone versus strain-specific loops

Directory of Open Access Journals (Sweden)

Gendrault-Jacquemard A

2005-07-01

Full Text Available Abstract Background Public databases now contain multitude of complete bacterial genomes, including several genomes of the same species. The available data offers new opportunities to address questions about bacterial genome evolution, a task that requires reliable fine comparison data of closely related genomes. Recent analyses have shown, using pairwise whole genome alignments, that it is possible to segment bacterial genomes into a common conserved backbone and strain-specific sequences called loops. Results Here, we generalize this approach and propose a strategy that allows systematic and non-biased genome segmentation based on multiple genome alignments. Segmentation analyses, as applied to 13 different bacterial species, confirmed the feasibility of our approach to discern the 'mosaic' organization of bacterial genomes. Segmentation results are available through a Web interface permitting functional analysis, extraction and visualization of the backbone/loops structure of documented genomes. To illustrate the potential of this approach, we performed a precise analysis of the mosaic organization of three E. coli strains and functional characterization of the loops. Conclusion The segmentation results including the backbone/loops structure of 13 bacterial species genomes are new and available for use by the scientific community at the URL: http://genome.jouy.inra.fr/mosaic.

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

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.

Plastid genome structure and loss of photosynthetic ability in the parasitic genus Cuscuta.

Science.gov (United States)

Revill, Meredith J W; Stanley, Susan; Hibberd, Julian M

2005-09-01

The genus Cuscuta (dodder) is composed of parasitic plants, some species of which appear to be losing the ability to photosynthesize. A molecular phylogeny was constructed using 15 species of Cuscuta in order to assess whether changes in photosynthetic ability and alterations in structure of the plastid genome relate to phylogenetic position within the genus. The molecular phylogeny provides evidence for four major clades within Cuscuta. Although DNA blot analysis showed that Cuscuta species have smaller plastid genomes than tobacco, and that plastome size varied significantly even within one Cuscuta clade, dot blot analysis indicated that the dodders possess homologous sequence to 101 genes from the tobacco plastome. Evidence is provided for significant rates of DNA transfer from plastid to nucleus in Cuscuta. Size and structure of Cuscuta plastid genomes, as well as photosynthetic ability, appear to vary independently of position within the phylogeny, thus supporting the hypothesis that within Cuscuta photosynthetic ability and organization of the plastid genome are changing in an unco-ordinated manner.

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

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).

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.

RNA 3D modules in genome-wide predictions of RNA 2D structure

DEFF Research Database (Denmark)

Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

2015-01-01

. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D......Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution...

Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches

Energy Technology Data Exchange (ETDEWEB)

Chandonia, John-Marc; Brenner, Steven E.

2004-07-14

The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small

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.

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.

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.

Functional Insights from Structural Genomics

Energy Technology Data Exchange (ETDEWEB)

Forouhar,F.; Kuzin, A.; Seetharaman, J.; Lee, I.; Zhou, W.; Abashidze, M.; Chen, Y.; Montelione, G.; Tong, L.; et al

2007-01-01

Structural genomics efforts have produced structural information, either directly or by modeling, for thousands of proteins over the past few years. While many of these proteins have known functions, a large percentage of them have not been characterized at the functional level. The structural information has provided valuable functional insights on some of these proteins, through careful structural analyses, serendipity, and structure-guided functional screening. Some of the success stories based on structures solved at the Northeast Structural Genomics Consortium (NESG) are reported here. These include a novel methyl salicylate esterase with important role in plant innate immunity, a novel RNA methyltransferase (H. influenzae yggJ (HI0303)), a novel spermidine/spermine N-acetyltransferase (B. subtilis PaiA), a novel methyltransferase or AdoMet binding protein (A. fulgidus AF{_}0241), an ATP:cob(I)alamin adenosyltransferase (B. subtilis YvqK), a novel carboxysome pore (E. coli EutN), a proline racemase homolog with a disrupted active site (B. melitensis BME11586), an FMN-dependent enzyme (S. pneumoniae SP{_}1951), and a 12-stranded {beta}-barrel with a novel fold (V. parahaemolyticus VPA1032).

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.

A sequence-based survey of the complex structural organization of tumor genomes

Energy Technology Data Exchange (ETDEWEB)

Collins, Colin; Raphael, Benjamin J.; Volik, Stanislav; Yu, Peng; Wu, Chunxiao; Huang, Guiqing; Linardopoulou, Elena V.; Trask, Barbara J.; Waldman, Frederic; Costello, Joseph; Pienta, Kenneth J.; Mills, Gordon B.; Bajsarowicz, Krystyna; Kobayashi, Yasuko; Sridharan, Shivaranjani; Paris, Pamela; Tao, Quanzhou; Aerni, Sarah J.; Brown, Raymond P.; Bashir, Ali; Gray, Joe W.; Cheng, Jan-Fang; de Jong, Pieter; Nefedov, Mikhail; Ried, Thomas; Padilla-Nash, Hesed M.; Collins, Colin C.

2008-04-03

The genomes of many epithelial tumors exhibit extensive chromosomal rearrangements. All classes of genome rearrangements can be identified using End Sequencing Profiling (ESP), which relies on paired-end sequencing of cloned tumor genomes. In this study, brain, breast, ovary and prostate tumors along with three breast cancer cell lines were surveyed with ESP yielding the largest available collection of sequence-ready tumor genome breakpoints and providing evidence that some rearrangements may be recurrent. Sequencing and fluorescence in situ hybridization (FISH) confirmed translocations and complex tumor genome structures that include coamplification and packaging of disparate genomic loci with associated molecular heterogeneity. Comparison of the tumor genomes suggests recurrent rearrangements. Some are likely to be novel structural polymorphisms, whereas others may be bona fide somatic rearrangements. A recurrent fusion transcript in breast tumors and a constitutional fusion transcript resulting from a segmental duplication were identified. Analysis of end sequences for single nucleotide polymorphisms (SNPs) revealed candidate somatic mutations and an elevated rate of novel SNPs in an ovarian tumor. These results suggest that the genomes of many epithelial tumors may be far more dynamic and complex than previously appreciated and that genomic fusions including fusion transcripts and proteins may be common, possibly yielding tumor-specific biomarkers and therapeutic targets.

Spectral entropy criteria for structural segmentation in genomic DNA sequences

International Nuclear Information System (INIS)

Chechetkin, V.R.; Lobzin, V.V.

2004-01-01

The spectral entropy is calculated with Fourier structure factors and characterizes the level of structural ordering in a sequence of symbols. It may efficiently be applied to the assessment and reconstruction of the modular structure in genomic DNA sequences. We present the relevant spectral entropy criteria for the local and non-local structural segmentation in DNA sequences. The results are illustrated with the model examples and analysis of intervening exon-intron segments in the protein-coding regions

A Confirmatory Factor Analysis of the Structure of Abbreviated Math Anxiety Scale

Directory of Open Access Journals (Sweden)

Farahman Farrokhi

2011-06-01

Full Text Available "nObjective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Abbreviated Math Anxiety Scale (AMAS, proposed by Hopko, Mahadevan, Bare & Hunt. "nMethod: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. The confirmatory factor analysis (CFA was carried out to determine the factor structures of the Persian version of AMAS. "nResults: As expected, the two-factor solution provided a better fit to the data than a single factor. Moreover, multi-group analyses showed that this two-factor structure was invariant across sex. Hence, AMAS provides an equally valid measure for use among college students. "nConclusions:  Brief AMAS demonstrates adequate reliability and validity. The AMAS scores can be used to compare symptoms of math anxiety between male and female students. The study both expands and adds support to the existing body of math anxiety literature.

Modelling concrete behaviour at early-age: multi-scale analysis and simulation of a massive disposal structure

International Nuclear Information System (INIS)

Honorio-De-Faria, Tulio

2015-01-01

The accurate prediction of the long and short-term behaviour of concrete structures in the nuclear domain is essential to ensure optimal performances (integrity, containment properties) during their service life. In the particular case of massive concrete structures, at early age the heat produced by hydration reactions cannot be evacuated fast enough so that high temperatures may be reached and the resulting gradients of temperature might lead to cracking according to the external and internal restraints to which the structures are subjected. The goals of this study are (1) to perform numerical simulations in order to describe and predict the thermo-chemo-mechanical behaviour at early-age of a massive concrete structure devoted to nuclear waste disposal on surface, and (2) to develop and apply up-scaling tools to estimate rigorously the key properties of concrete needed in an early-age analysis from the composition of the material. Firstly, a chemo-thermal analysis aims at determining the influence of convection, solar radiation, re-radiation and hydration heat on the thermal response of the structure. Practical recommendations regarding concreting temperatures are provided in order to limit the maximum temperature reached within the structure. Then, by means of a mechanical analysis, simplified and more complex (i.e. accounting for coupled creep and damage) modelling strategies are used to assess scenarios involving different boundary conditions defined from the previous chemo-thermal analysis. Secondly, a study accounting for the multi-scale character of concrete is performed. A simplified model of cement hydration kinetics is proposed. The evolution of the different phases at the cement paste level can be estimated. Then, analytical and numerical tools to upscale the ageing properties are presented and applied to estimate the mechanical and thermal properties of cement based materials. Finally, the input data used in the structural analysis are compared with

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.

Insight into dynamic genome imaging: Canonical framework identification and high-throughput analysis.

Science.gov (United States)

Ronquist, Scott; Meixner, Walter; Rajapakse, Indika; Snyder, John

2017-07-01

The human genome is dynamic in structure, complicating researcher's attempts at fully understanding it. Time series "Fluorescent in situ Hybridization" (FISH) imaging has increased our ability to observe genome structure, but due to cell type and experimental variability this data is often noisy and difficult to analyze. Furthermore, computational analysis techniques are needed for homolog discrimination and canonical framework detection, in the case of time-series images. In this paper we introduce novel ideas for nucleus imaging analysis, present findings extracted using dynamic genome imaging, and propose an objective algorithm for high-throughput, time-series FISH imaging. While a canonical framework could not be detected beyond statistical significance in the analyzed dataset, a mathematical framework for detection has been outlined with extension to 3D image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

Insights into structural variations and genome rearrangements in prokaryotic genomes.

Science.gov (United States)

Periwal, Vinita; Scaria, Vinod

2015-01-01

Structural variations (SVs) are genomic rearrangements that affect fairly large fragments of DNA. Most of the SVs such as inversions, deletions and translocations have been largely studied in context of genetic diseases in eukaryotes. However, recent studies demonstrate that genome rearrangements can also have profound impact on prokaryotic genomes, leading to altered cell phenotype. In contrast to single-nucleotide variations, SVs provide a much deeper insight into organization of bacterial genomes at a much better resolution. SVs can confer change in gene copy number, creation of new genes, altered gene expression and many other functional consequences. High-throughput technologies have now made it possible to explore SVs at a much refined resolution in bacterial genomes. Through this review, we aim to highlight the importance of the less explored field of SVs in prokaryotic genomes and their impact. We also discuss its potential applicability in the emerging fields of synthetic biology and genome engineering where targeted SVs could serve to create sophisticated and accurate genome editing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative Phylogenetic Analysis

Directory of Open Access Journals (Sweden)

Anne Busch

2018-03-01

Full Text Available Francisella (F. tularensis is a highly virulent, Gram-negative bacterial pathogen and the causative agent of the zoonotic disease tularemia. Here, we generated, analyzed and characterized a high quality circular genome sequence of the F. tularensis subsp. holarctica strain 12T0050 that caused fatal tularemia in a hare. Besides the genomic structure, we focused on the analysis of oriC, unique to the Francisella genus and regulating replication in and outside hosts and the first report on genomic DNA methylation of a Francisella strain. The high quality genome was used to establish and evaluate a diagnostic whole genome sequencing pipeline. A genotyping strategy for F. tularensis was developed using various bioinformatics tools for genotyping. Additionally, whole genome sequences of F. tularensis subsp. holarctica isolates isolated in the years 2008–2015 in Germany were generated. A phylogenetic analysis allowed to determine the genetic relatedness of these isolates and confirmed the highly conserved nature of F. tularensis subsp. holarctica.

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.

Genome-wide analysis of LTR-retrotransposons in oil palm.

Science.gov (United States)

Beulé, Thierry; Agbessi, Mawussé Dt; Dussert, Stephane; Jaligot, Estelle; Guyot, Romain

2015-10-15

The oil palm (Elaeis guineensis Jacq.) is a major cultivated crop and the world's largest source of edible vegetable oil. The genus Elaeis comprises two species E. guineensis, the commercial African oil palm and E. oleifera, which is used in oil palm genetic breeding. The recent publication of both the African oil palm genome assembly and the first draft sequence of its Latin American relative now allows us to tackle the challenge of understanding the genome composition, structure and evolution of these palm genomes through the annotation of their repeated sequences. In this study, we identified, annotated and compared Transposable Elements (TE) from the African and Latin American oil palms. In a first step, Transposable Element databases were built through de novo detection in both genome sequences then the TE content of both genomes was estimated. Then putative full-length retrotransposons with Long Terminal Repeats (LTRs) were further identified in the E. guineensis genome for characterization of their structural diversity, copy number and chromosomal distribution. Finally, their relative expression in several tissues was determined through in silico analysis of publicly available transcriptome data. Our results reveal a congruence in the transpositional history of LTR retrotransposons between E. oleifera and E. guineensis, especially the Sto-4 family. Also, we have identified and described 583 full-length LTR-retrotransposons in the Elaeis guineensis genome. Our work shows that these elements are most likely no longer mobile and that no recent insertion event has occurred. Moreover, the analysis of chromosomal distribution suggests a preferential insertion of Copia elements in gene-rich regions, whereas Gypsy elements appear to be evenly distributed throughout the genome. Considering the high proportion of LTR retrotransposon in the oil palm genome, our work will contribute to a greater understanding of their impact on genome organization and evolution

Body maps on the human genome.

Science.gov (United States)

Cherniak, Christopher; Rodriguez-Esteban, Raul

2013-12-20

Chromosomes have territories, or preferred locales, in the cell nucleus. When these sites are taken into account, some large-scale structure of the human genome emerges. The synoptic picture is that genes highly expressed in particular topologically compact tissues are not randomly distributed on the genome. Rather, such tissue-specific genes tend to map somatotopically onto the complete chromosome set. They seem to form a "genome homunculus": a multi-dimensional, genome-wide body representation extending across chromosome territories of the entire spermcell nucleus. The antero-posterior axis of the body significantly corresponds to the head-tail axis of the nucleus, and the dorso-ventral body axis to the central-peripheral nucleus axis. This large-scale genomic structure includes thousands of genes. One rationale for a homuncular genome structure would be to minimize connection costs in genetic networks. Somatotopic maps in cerebral cortex have been reported for over a century.

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

Neandertal admixture in Eurasia confirmed by maximum-likelihood analysis of three genomes.

Science.gov (United States)

Lohse, Konrad; Frantz, Laurent A F

2014-04-01

Although there has been much interest in estimating histories of divergence and admixture from genomic data, it has proved difficult to distinguish recent admixture from long-term structure in the ancestral population. Thus, recent genome-wide analyses based on summary statistics have sparked controversy about the possibility of interbreeding between Neandertals and modern humans in Eurasia. Here we derive the probability of full mutational configurations in nonrecombining sequence blocks under both admixture and ancestral structure scenarios. Dividing the genome into short blocks gives an efficient way to compute maximum-likelihood estimates of parameters. We apply this likelihood scheme to triplets of human and Neandertal genomes and compare the relative support for a model of admixture from Neandertals into Eurasian populations after their expansion out of Africa against a history of persistent structure in their common ancestral population in Africa. Our analysis allows us to conclusively reject a model of ancestral structure in Africa and instead reveals strong support for Neandertal admixture in Eurasia at a higher rate (3.4-7.3%) than suggested previously. Using analysis and simulations we show that our inference is more powerful than previous summary statistics and robust to realistic levels of recombination.

Evaluation of ground motion scaling methods for analysis of structural systems

Science.gov (United States)

O'Donnell, A. P.; Beltsar, O.A.; Kurama, Y.C.; Kalkan, E.; Taflanidis, A.A.

2011-01-01

Ground motion selection and scaling comprises undoubtedly the most important component of any seismic risk assessment study that involves time-history analysis. Ironically, this is also the single parameter with the least guidance provided in current building codes, resulting in the use of mostly subjective choices in design. The relevant research to date has been primarily on single-degree-of-freedom systems, with only a few studies using multi-degree-of-freedom systems. Furthermore, the previous research is based solely on numerical simulations with no experimental data available for the validation of the results. By contrast, the research effort described in this paper focuses on an experimental evaluation of selected ground motion scaling methods based on small-scale shake-table experiments of re-configurable linearelastic and nonlinear multi-story building frame structure models. Ultimately, the experimental results will lead to the development of guidelines and procedures to achieve reliable demand estimates from nonlinear response history analysis in seismic design. In this paper, an overview of this research effort is discussed and preliminary results based on linear-elastic dynamic response are presented. ?? ASCE 2011.

Macromolecular structure determination in the post-genome era

CERN Document Server

Kuhn, P

2001-01-01

Recent advances in genetics, molecular biology and crystallographic instrumentation and methodology have led to a revolution in the field of Structural Molecular Biology (SMB). These combined advances have paved the way to a more complete and detailed understanding of the biological macromolecules that make up an organism, both in terms of their individual functions and also the interactions between them. In this paper we describe a large-scale, genomic approach to the three-dimensional structure determination of macromolecules and their complexes, using high-throughput methodology to streamline all aspects of the process. This task requires the development of automated high-intensity synchrotron beam lines for X-ray diffraction data collection from single crystal samples. Furthermore, these beam lines must be operated within a sophisticated software and hardware environment, which is capable of delivering a completely automated structure determination pipeline. The SMB resource at SSRL is developing a system...

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

RNA structural constraints in the evolution of the influenza A virus genome NP segment

NARCIS (Netherlands)

A.P. Gultyaev (Alexander); A. Tsyganov-Bodounov (Anton); M.I. Spronken (Monique); S. Van Der Kooij (Sander); R.A.M. Fouchier (Ron); R.C.L. Olsthoorn (René)

2014-01-01

textabstractConserved RNA secondary structures were predicted in the nucleoprotein (NP) segment of the influenza A virus genome using comparative sequence and structure analysis. A number of structural elements exhibiting nucleotide covariations were identified over the whole segment length,

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.

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.

Improvisation in evolution of genes and genomes: whose structure is it anyway?

Science.gov (United States)

Shakhnovich, Boris E; Shakhnovich, Eugene I

2008-06-01

Significant progress has been made in recent years in a variety of seemingly unrelated fields such as sequencing, protein structure prediction, and high-throughput transcriptomics and metabolomics. At the same time, new microscopic models have been developed that made it possible to analyze the evolution of genes and genomes from first principles. The results from these efforts enable, for the first time, a comprehensive insight into the evolution of complex systems and organisms on all scales--from sequences to organisms and populations. Every newly sequenced genome uncovers new genes, families, and folds. Where do these new genes come from? How do gene duplication and subsequent divergence of sequence and structure affect the fitness of the organism? What role does regulation play in the evolution of proteins and folds? Emerging synergism between data and modeling provides first robust answers to these questions.

Comprehensive Genome Analysis of Carbapenemase-Producing Enterobacter spp.: New Insights into Phylogeny, Population Structure, and Resistance Mechanisms.

Science.gov (United States)

Chavda, Kalyan D; Chen, Liang; Fouts, Derrick E; Sutton, Granger; Brinkac, Lauren; Jenkins, Stephen G; Bonomo, Robert A; Adams, Mark D; Kreiswirth, Barry N

2016-12-13

Knowledge regarding the genomic structure of Enterobacter spp., the second most prevalent carbapenemase-producing Enterobacteriaceae, remains limited. Here we sequenced 97 clinical Enterobacter species isolates that were both carbapenem susceptible and resistant from various geographic regions to decipher the molecular origins of carbapenem resistance and to understand the changing phylogeny of these emerging and drug-resistant pathogens. Of the carbapenem-resistant isolates, 30 possessed bla KPC-2 , 40 had bla KPC-3 , 2 had bla KPC-4 , and 2 had bla NDM-1 Twenty-three isolates were carbapenem susceptible. Six genomes were sequenced to completion, and their sizes ranged from 4.6 to 5.1 Mbp. Phylogenomic analysis placed 96 of these genomes, 351 additional Enterobacter genomes downloaded from NCBI GenBank, and six newly sequenced type strains into 19 phylogenomic groups-18 groups (A to R) in the Enterobacter cloacae complex and Enterobacter aerogenes Diverse mechanisms underlying the molecular evolutionary trajectory of these drug-resistant Enterobacter spp. were revealed, including the acquisition of an antibiotic resistance plasmid, followed by clonal spread, horizontal transfer of bla KPC -harboring plasmids between different phylogenomic groups, and repeated transposition of the bla KPC gene among different plasmid backbones. Group A, which comprises multilocus sequence type 171 (ST171), was the most commonly identified (23% of isolates). Genomic analysis showed that ST171 isolates evolved from a common ancestor and formed two different major clusters; each acquiring unique bla KPC -harboring plasmids, followed by clonal expansion. The data presented here represent the first comprehensive study of phylogenomic interrogation and the relationship between antibiotic resistance and plasmid discrimination among carbapenem-resistant Enterobacter spp., demonstrating the genetic diversity and complexity of the molecular mechanisms driving antibiotic resistance in this

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...

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.

Deep transcriptome sequencing provides new insights into the structural and functional organization of the wheat genome.

Science.gov (United States)

Pingault, Lise; Choulet, Frédéric; Alberti, Adriana; Glover, Natasha; Wincker, Patrick; Feuillet, Catherine; Paux, Etienne

2015-02-10

Because of its size, allohexaploid nature, and high repeat content, the bread wheat genome is a good model to study the impact of the genome structure on gene organization, function, and regulation. However, because of the lack of a reference genome sequence, such studies have long been hampered and our knowledge of the wheat gene space is still limited. The access to the reference sequence of the wheat chromosome 3B provided us with an opportunity to study the wheat transcriptome and its relationships to genome and gene structure at a level that has never been reached before. By combining this sequence with RNA-seq data, we construct a fine transcriptome map of the chromosome 3B. More than 8,800 transcription sites are identified, that are distributed throughout the entire chromosome. Expression level, expression breadth, alternative splicing as well as several structural features of genes, including transcript length, number of exons, and cumulative intron length are investigated. Our analysis reveals a non-monotonic relationship between gene expression and structure and leads to the hypothesis that gene structure is determined by its function, whereas gene expression is subject to energetic cost. Moreover, we observe a recombination-based partitioning at the gene structure and function level. Our analysis provides new insights into the relationships between gene and genome structure and function. It reveals mechanisms conserved with other plant species as well as superimposed evolutionary forces that shaped the wheat gene space, likely participating in wheat adaptation.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

Science.gov (United States)

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

Structural genomic variations and Parkinson's disease.

Science.gov (United States)

Bandrés-Ciga, Sara; Ruz, Clara; Barrero, Francisco J; Escamilla-Sevilla, Francisco; Pelegrina, Javier; Vives, Francisco; Duran, Raquel

2017-10-01

Parkinson's disease (PD) is the second most common neurodegenerative disease, whose prevalence is projected to be between 8.7 and 9.3 million by 2030. Until about 20 years ago, PD was considered to be the textbook example of a "non-genetic" disorder. Nowadays, PD is generally considered a multifactorial disorder that arises from the combination and complex interaction of genes and environmental factors. To date, a total of 7 genes including SNCA, LRRK2, PARK2, DJ-1, PINK 1, VPS35 and ATP13A2 have been seen to cause unequivocally Mendelian PD. Also, variants with incomplete penetrance in the genes LRRK2 and GBA are considered to be strong risk factors for PD worldwide. Although genetic studies have provided valuable insights into the pathogenic mechanisms underlying PD, the role of structural variation in PD has been understudied in comparison with other genomic variations. Structural genomic variations might substantially account for such genetic substrates yet to be discovered. The present review aims to provide an overview of the structural genomic variants implicated in the pathogenesis of PD.

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.

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.

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

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

Nonlinear Analysis and Scaling Laws for Noncircular Composite Structures Subjected to Combined Loads

Science.gov (United States)

Hilburger, Mark W.; Rose, Cheryl A.; Starnes, James H., Jr.

2001-01-01

Results from an analytical study of the response of a built-up, multi-cell noncircular composite structure subjected to combined internal pressure and mechanical loads are presented. Nondimensional parameters and scaling laws based on a first-order shear-deformation plate theory are derived for this noncircular composite structure. The scaling laws are used to design sub-scale structural models for predicting the structural response of a full-scale structure representative of a portion of a blended-wing-body transport aircraft. Because of the complexity of the full-scale structure, some of the similitude conditions are relaxed for the sub-scale structural models. Results from a systematic parametric study are used to determine the effects of relaxing selected similitude conditions on the sensitivity of the effectiveness of using the sub-scale structural model response characteristics for predicting the full-scale structure response characteristics.

Grass genomes

OpenAIRE

Bennetzen, Jeffrey L.; SanMiguel, Phillip; Chen, Mingsheng; Tikhonov, Alexander; Francki, Michael; Avramova, Zoya

1998-01-01

For the most part, studies of grass genome structure have been limited to the generation of whole-genome genetic maps or the fine structure and sequence analysis of single genes or gene clusters. We have investigated large contiguous segments of the genomes of maize, sorghum, and rice, primarily focusing on intergenic spaces. Our data indicate that much (>50%) of the maize genome is composed of interspersed repetitive DNAs, primarily nested retrotransposons that in...

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.

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

Structural dynamics of retroviral genome and the packaging.

Science.gov (United States)

Miyazaki, Yasuyuki; Miyake, Ariko; Nomaguchi, Masako; Adachi, Akio

2011-01-01

Retroviruses can cause diseases such as AIDS, leukemia, and tumors, but are also used as vectors for human gene therapy. All retroviruses, except foamy viruses, package two copies of unspliced genomic RNA into their progeny viruses. Understanding the molecular mechanisms of retroviral genome packaging will aid the design of new anti-retroviral drugs targeting the packaging process and improve the efficacy of retroviral vectors. Retroviral genomes have to be specifically recognized by the cognate nucleocapsid domain of the Gag polyprotein from among an excess of cellular and spliced viral mRNA. Extensive virological and structural studies have revealed how retroviral genomic RNA is selectively packaged into the viral particles. The genomic area responsible for the packaging is generally located in the 5' untranslated region (5' UTR), and contains dimerization site(s). Recent studies have shown that retroviral genome packaging is modulated by structural changes of RNA at the 5' UTR accompanied by the dimerization. In this review, we focus on three representative retroviruses, Moloney murine leukemia virus, human immunodeficiency virus type 1 and 2, and describe the molecular mechanism of retroviral genome packaging.

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.

Multidimensional scaling for large genomic data sets

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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

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

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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.

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

Gene design, cloning and protein-expression methods for high-value targets at the Seattle Structural Genomics Center for Infectious Disease

International Nuclear Information System (INIS)

Raymond, Amy; Haffner, Taryn; Ng, Nathan; Lorimer, Don; Staker, Bart; Stewart, Lance

2011-01-01

An overview of one salvage strategy for high-value SSGCID targets is given. Any structural genomics endeavor, particularly ambitious ones such as the NIAID-funded Seattle Structural Genomics Center for Infectious Disease (SSGCID) and Center for Structural Genomics of Infectious Disease (CSGID), face technical challenges at all points of the production pipeline. One salvage strategy employed by SSGCID is combined gene engineering and structure-guided construct design to overcome challenges at the levels of protein expression and protein crystallization. Multiple constructs of each target are cloned in parallel using Polymerase Incomplete Primer Extension cloning and small-scale expressions of these are rapidly analyzed by capillary electrophoresis. Using the methods reported here, which have proven particularly useful for high-value targets, otherwise intractable targets can be resolved

Comparative analysis of catfish BAC end sequences with the zebrafish genome

Directory of Open Access Journals (Sweden)

Abernathy Jason

2009-12-01

Full Text Available Abstract Background Comparative mapping is a powerful tool to transfer genomic information from sequenced genomes to closely related species for which whole genome sequence data are not yet available. However, such an approach is still very limited in catfish, the most important aquaculture species in the United States. This project was initiated to generate additional BAC end sequences and demonstrate their applications in comparative mapping in catfish. Results We reported the generation of 43,000 BAC end sequences and their applications for comparative genome analysis in catfish. Using these and the additional 20,000 existing BAC end sequences as a resource along with linkage mapping and existing physical map, conserved syntenic regions were identified between the catfish and zebrafish genomes. A total of 10,943 catfish BAC end sequences (17.3% had significant BLAST hits to the zebrafish genome (cutoff value ≤ e-5, of which 3,221 were unique gene hits, providing a platform for comparative mapping based on locations of these genes in catfish and zebrafish. Genetic linkage mapping of microsatellites associated with contigs allowed identification of large conserved genomic segments and construction of super scaffolds. Conclusion BAC end sequences and their associated polymorphic markers are great resources for comparative genome analysis in catfish. Highly conserved chromosomal regions were identified to exist between catfish and zebrafish. However, it appears that the level of conservation at local genomic regions are high while a high level of chromosomal shuffling and rearrangements exist between catfish and zebrafish genomes. Orthologous regions established through comparative analysis should facilitate both structural and functional genome analysis in catfish.

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

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.

Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants.

Directory of Open Access Journals (Sweden)

Jiang Du

2009-07-01

Full Text Available The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen, with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs. SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome. To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of

The First Complete Chloroplast Genome Sequences in Actinidiaceae: Genome Structure and Comparative Analysis.

Science.gov (United States)

Yao, Xiaohong; Tang, Ping; Li, Zuozhou; Li, Dawei; Liu, Yifei; Huang, Hongwen

2015-01-01

Actinidia chinensis is an important economic plant belonging to the basal lineage of the asterids. Availability of a complete Actinidia chloroplast genome sequence is crucial to understanding phylogenetic relationships among major lineages of angiosperms and facilitates kiwifruit genetic improvement. We report here the complete nucleotide sequences of the chloroplast genomes for Actinidia chinensis and A. chinensis var deliciosa obtained through de novo assembly of Illumina paired-end reads produced by total DNA sequencing. The total genome size ranges from 155,446 to 157,557 bp, with an inverted repeat (IR) of 24,013 to 24,391 bp, a large single copy region (LSC) of 87,984 to 88,337 bp and a small single copy region (SSC) of 20,332 to 20,336 bp. The genome encodes 113 different genes, including 79 unique protein-coding genes, 30 tRNA genes and 4 ribosomal RNA genes, with 16 duplicated in the inverted repeats, and a tRNA gene (trnfM-CAU) duplicated once in the LSC region. Comparisons of IR boundaries among four asterid species showed that IR/LSC borders were extended into the 5' portion of the psbA gene and IR contraction occurred in Actinidia. The clap gene has been lost from the chloroplast genome in Actinidia, and may have been transferred to the nucleus during chloroplast evolution. Twenty-seven polymorphic simple sequence repeat (SSR) loci were identified in the Actinidia chloroplast genome. Maximum parsimony analyses of a 72-gene, 16 taxa angiosperm dataset strongly support the placement of Actinidiaceae in Ericales within the basal asterids.

GeneViTo: Visualizing gene-product functional and structural features in genomic datasets

Directory of Open Access Journals (Sweden)

Promponas Vasilis J

2003-10-01

Full Text Available Abstract Background The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. Results GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. Conclusions GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating

Structural determinants and mechanism of HIV-1 genome packaging.

Science.gov (United States)

Lu, Kun; Heng, Xiao; Summers, Michael F

2011-07-22

Like all retroviruses, the human immunodeficiency virus selectively packages two copies of its unspliced RNA genome, both of which are utilized for strand-transfer-mediated recombination during reverse transcription-a process that enables rapid evolution under environmental and chemotherapeutic pressures. The viral RNA appears to be selected for packaging as a dimer, and there is evidence that dimerization and packaging are mechanistically coupled. Both processes are mediated by interactions between the nucleocapsid domains of a small number of assembling viral Gag polyproteins and RNA elements within the 5'-untranslated region of the genome. A number of secondary structures have been predicted for regions of the genome that are responsible for packaging, and high-resolution structures have been determined for a few small RNA fragments and protein-RNA complexes. However, major questions regarding the RNA structures (and potentially the structural changes) that are responsible for dimeric genome selection remain unanswered. Here, we review efforts that have been made to identify the molecular determinants and mechanism of human immunodeficiency virus type 1 genome packaging. Copyright © 2011 Elsevier Ltd. All rights reserved.

Analysis of high-identity segmental duplications in the grapevine genome

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Carelli Francesco N

2011-08-01

Full Text Available Abstract Background Segmental duplications (SDs are blocks of genomic sequence of 1-200 kb that map to different loci in a genome and share a sequence identity > 90%. SDs show at the sequence level the same characteristics as other regions of the human genome: they contain both high-copy repeats and gene sequences. SDs play an important role in genome plasticity by creating new genes and modeling genome structure. Although data is plentiful for mammals, not much was known about the representation of SDs in plant genomes. In this regard, we performed a genome-wide analysis of high-identity SDs on the sequenced grapevine (Vitis vinifera genome (PN40024. Results We demonstrate that recent SDs (> 94% identity and >= 10 kb in size are a relevant component of the grapevine genome (85 Mb, 17% of the genome sequence. We detected mitochondrial and plastid DNA and genes (10% of gene annotation in segmentally duplicated regions of the nuclear genome. In particular, the nine highest copy number genes have a copy in either or both organelle genomes. Further we showed that several duplicated genes take part in the biosynthesis of compounds involved in plant response to environmental stress. Conclusions These data show the great influence of SDs and organelle DNA transfers in modeling the Vitis vinifera nuclear DNA structure as well as the impact of SDs in contributing to the adaptive capacity of grapevine and the nutritional content of grape products through genome variation. This study represents a step forward in the full characterization of duplicated genes important for grapevine cultural needs and human health.

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

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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.

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

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Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2018-03-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.

The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

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Zheng Wang

Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

Genetic diversity and structure of elite cotton germplasm (Gossypium hirsutum L.) using genome-wide SNP data.

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Ai, XianTao; Liang, YaJun; Wang, JunDuo; Zheng, JuYun; Gong, ZhaoLong; Guo, JiangPing; Li, XueYuan; Qu, YanYing

2017-10-01

Cotton (Gossypium spp.) is the most important natural textile fiber crop, and Gossypium hirsutum L. is responsible for 90% of the annual cotton crop in the world. Information on cotton genetic diversity and population structure is essential for new breeding lines. In this study, we analyzed population structure and genetic diversity of 288 elite Gossypium hirsutum cultivar accessions collected from around the world, and especially from China, using genome-wide single nucleotide polymorphisms (SNP) markers. The average polymorphsim information content (PIC) was 0.25, indicating a relatively low degree of genetic diversity. Population structure analysis revealed extensive admixture and identified three subgroups. Phylogenetic analysis supported the subgroups identified by STRUCTURE. The results from both population structure and phylogenetic analysis were, for the most part, in agreement with pedigree information. Analysis of molecular variance revealed a larger amount of variation was due to diversity within the groups. Establishment of genetic diversity and population structure from this study could be useful for genetic and genomic analysis and systematic utilization of the standing genetic variation in upland cotton.

Structural Genomics of Minimal Organisms: Pipeline and Results

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung-Hou; Shin, Dong-Hae; Kim, Rosalind; Adams, Paul; Chandonia, John-Marc

2007-09-14

The initial objective of the Berkeley Structural Genomics Center was to obtain a near complete three-dimensional (3D) structural information of all soluble proteins of two minimal organisms, closely related pathogens Mycoplasma genitalium and M. pneumoniae. The former has fewer than 500 genes and the latter has fewer than 700 genes. A semiautomated structural genomics pipeline was set up from target selection, cloning, expression, purification, and ultimately structural determination. At the time of this writing, structural information of more than 93percent of all soluble proteins of M. genitalium is avail able. This chapter summarizes the approaches taken by the authors' center.

GenRGenS: Software for Generating Random Genomic Sequences and Structures

OpenAIRE

Ponty , Yann; Termier , Michel; Denise , Alain

2006-01-01

International audience; GenRGenS is a software tool dedicated to randomly generating genomic sequences and structures. It handles several classes of models useful for sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions and PROSITE expressions. GenRGenS is the only program that can handle weighted context-free grammars, thus allowing the user to model and to generate structured objects (such as RNA secondary structures) of any giv...

Structural dynamics of retroviral genome and the packaging

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Yasuyuki eMiyazaki

2011-12-01

Full Text Available Retroviruses can cause diseases such as AIDS, leukemia and tumors, but are also used as vectors for human gene therapy. All retroviruses, except foamy viruses, package two copies of unspliced genomic RNA into their progeny viruses. Understanding the molecular mechanisms of retroviral genome packaging will aid the design of new anti-retroviral drugs targeting the packaging process and improve the efficacy of retroviral vectors. Retroviral genomes have to be specifically recognized by the cognate nucleocapsid (NC domain of the Gag polyprotein from among an excess of cellular and spliced viral mRNA. Extensive virological and structural studies have revealed how retroviral genomic RNA is selectively packaged into the viral particles. The genomic area responsible for the packaging is generally located in the 5’ untranslated region (5’ UTR, and contains dimerization site(s. Recent studies have shown that retroviral genome packaging is modulated by structural changes of RNA at the 5’ UTR accompanied by the dimerization. In this review, we focus on three representative retroviruses, Moloney murine leukemia virus (MoMLV, human immunodeficiency virus type 1 (HIV-1 and 2 (HIV-2, and describe the molecular mechanism of retroviral genome packaging.

Structural constraints in the packaging of bluetongue virus genomic segments.

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Burkhardt, Christiane; Sung, Po-Yu; Celma, Cristina C; Roy, Polly

2014-10-01

The mechanism used by bluetongue virus (BTV) to ensure the sorting and packaging of its 10 genomic segments is still poorly understood. In this study, we investigated the packaging constraints for two BTV genomic segments from two different serotypes. Segment 4 (S4) of BTV serotype 9 was mutated sequentially and packaging of mutant ssRNAs was investigated by two newly developed RNA packaging assay systems, one in vivo and the other in vitro. Modelling of the mutated ssRNA followed by biochemical data analysis suggested that a conformational motif formed by interaction of the 5' and 3' ends of the molecule was necessary and sufficient for packaging. A similar structural signal was also identified in S8 of BTV serotype 1. Furthermore, the same conformational analysis of secondary structures for positive-sense ssRNAs was used to generate a chimeric segment that maintained the putative packaging motif but contained unrelated internal sequences. This chimeric segment was packaged successfully, confirming that the motif identified directs the correct packaging of the segment. © 2014 The Authors.

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...

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

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Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

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

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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.

Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments

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Trojan, Daniela; Roux, Simon; Herbold, Craig; Rattei, Thomas; Woebken, Dagmar

2018-01-01

Summary Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large‐scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 (n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low‐ and high‐affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected – both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H2, now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large‐scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment. PMID:29327410

XTHs from Fragaria vesca: genomic structure and transcriptomic analysis in ripening fruit and other tissues.

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Opazo, María Cecilia; Lizana, Rodrigo; Stappung, Yazmina; Davis, Thomas M; Herrera, Raúl; Moya-León, María Alejandra

2017-11-07

Fragaria vesca or 'woodland strawberry' has emerged as an attractive model for the study of ripening of non-climacteric fruit. It has several advantages, such as its small genome and its diploidy. The recent availability of the complete sequence of its genome opens the possibility for further analysis and its use as a reference species. Fruit softening is a physiological event and involves many biochemical changes that take place at the final stages of fruit development; among them, the remodeling of cell walls by the action of a set of enzymes. Xyloglucan endotransglycosylase/hydrolase (XTH) is a cell wall-associated enzyme, which is encoded by a multigene family. Its action modifies the structure of xyloglucans, a diverse group of polysaccharides that crosslink with cellulose microfibrills, affecting therefore the functional structure of the cell wall. The aim of this work is to identify the XTH-encoding genes present in F. vesca and to determine its transcription level in ripening fruit. The search resulted in identification of 26 XTH-encoding genes named as FvXTHs. Genetic structure and phylogenetic analyses were performed allowing the classification of FvXTH genes into three phylogenetic groups: 17 in group I/II, 2 in group IIIA and 4 in group IIIB. Two sequences were included into the ancestral group. Through a comparative analysis, characteristic structural protein domains were found in FvXTH protein sequences. In complement, expression analyses of FvXTHs by qPCR were performed in fruit at different developmental and ripening stages, as well as, in other tissues. The results showed a diverse expression pattern of FvXTHs in several tissues, although most of them are highly expressed in roots. Their expression patterns are not related to their respective phylogenetic groups. In addition, most FvXTHs are expressed in ripe fruit, and interestingly, some of them (FvXTH 18 and 20, belonging to phylogenic group I/II, and FvXTH 25 and 26 to group IIIB) display an

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

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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/.

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

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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.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

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Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

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.

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

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...

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

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.

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

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Wang Jintu

2011-04-01

,100 microsyntenies, covering over 50% of the zebrafish genome. BES of common carp are tremendous tools for comparative mapping between the two closely related species, zebrafish and common carp, which should facilitate both structural and functional genome analysis in common carp.

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

Science.gov (United States)

2011-01-01

the zebrafish genome. BES of common carp are tremendous tools for comparative mapping between the two closely related species, zebrafish and common carp, which should facilitate both structural and functional genome analysis in common carp. PMID:21492448

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.

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.

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

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

Macromolecular structure determination in the post-genome era

International Nuclear Information System (INIS)

Kuhn, P.; Soltis, S.M.

2001-01-01

Recent advances in genetics, molecular biology and crystallographic instrumentation and methodology have led to a revolution in the field of Structural Molecular Biology (SMB). These combined advances have paved the way to a more complete and detailed understanding of the biological macromolecules that make up an organism, both in terms of their individual functions and also the interactions between them. In this paper we describe a large-scale, genomic approach to the three-dimensional structure determination of macromolecules and their complexes, using high-throughput methodology to streamline all aspects of the process. This task requires the development of automated high-intensity synchrotron beam lines for X-ray diffraction data collection from single crystal samples. Furthermore, these beam lines must be operated within a sophisticated software and hardware environment, which is capable of delivering a completely automated structure determination pipeline. The SMB resource at SSRL is developing a system for the structure determination steps of this process, starting with the initial characterization of the frozen sample, followed by data collection, data reduction, phase determination, and model building. This paper focuses on the data collection elements of this high-throughput system

Analysis of ground response data at Lotung large-scale soil- structure interaction experiment site

International Nuclear Information System (INIS)

Chang, C.Y.; Mok, C.M.; Power, M.S.

1991-12-01

The Electric Power Research Institute (EPRI), in cooperation with the Taiwan Power Company (TPC), constructed two models (1/4-scale and 1/2-scale) of a nuclear plant containment structure at a site in Lotung (Tang, 1987), a seismically active region in northeast Taiwan. The models were constructed to gather data for the evaluation and validation of soil-structure interaction (SSI) analysis methodologies. Extensive instrumentation was deployed to record both structural and ground responses at the site during earthquakes. The experiment is generally referred to as the Lotung Large-Scale Seismic Test (LSST). As part of the LSST, two downhole arrays were installed at the site to record ground motions at depths as well as at the ground surface. Structural response and ground response have been recorded for a number of earthquakes (i.e. a total of 18 earthquakes in the period of October 1985 through November 1986) at the LSST site since the completion of the installation of the downhole instruments in October 1985. These data include those from earthquakes having magnitudes ranging from M L 4.5 to M L 7.0 and epicentral distances range from 4.7 km to 77.7 km. Peak ground surface accelerations range from 0.03 g to 0.21 g for the horizontal component and from 0.01 g to 0.20 g for the vertical component. The objectives of the study were: (1) to obtain empirical data on variations of earthquake ground motion with depth; (2) to examine field evidence of nonlinear soil response due to earthquake shaking and to determine the degree of soil nonlinearity; (3) to assess the ability of ground response analysis techniques including techniques to approximate nonlinear soil response to estimate ground motions due to earthquake shaking; and (4) to analyze earth pressures recorded beneath the basemat and on the side wall of the 1/4 scale model structure during selected earthquakes

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...

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.

Alignment-free comparative genomic screen for structured RNAs using coarse-grained secondary structure dot plots

DEFF Research Database (Denmark)

Kato, Yuki; Gorodkin, Jan; Havgaard, Jakob Hull

2017-01-01

. Methods: Here we present a fast and efficient method, DotcodeR, for detecting structurally similar RNAs in genomic sequences by comparing their corresponding coarse-grained secondary structure dot plots at string level. This allows us to perform an all-against-all scan of all window pairs from two genomes...... without alignment. Results: Our computational experiments with simulated data and real chromosomes demonstrate that the presented method has good sensitivity. Conclusions: DotcodeR can be useful as a pre-filter in a genomic comparative scan for structured RNAs....

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

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.

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

Genome Modeling System: A Knowledge Management Platform for Genomics.

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Malachi Griffith

2015-07-01

Full Text Available In this work, we present the Genome Modeling System (GMS, an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395 and matched lymphoblastoid line (HCC1395BL. These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Genomic structural variation contributes to phenotypic change of industrial bioethanol yeast Saccharomyces cerevisiae.

Science.gov (United States)

Zhang, Ke; Zhang, Li-Jie; Fang, Ya-Hong; Jin, Xin-Na; Qi, Lei; Wu, Xue-Chang; Zheng, Dao-Qiong

2016-03-01

Genomic structural variation (GSV) is a ubiquitous phenomenon observed in the genomes of Saccharomyces cerevisiae strains with different genetic backgrounds; however, the physiological and phenotypic effects of GSV are not well understood. Here, we first revealed the genetic characteristics of a widely used industrial S. cerevisiae strain, ZTW1, by whole genome sequencing. ZTW1 was identified as an aneuploidy strain and a large-scale GSV was observed in the ZTW1 genome compared with the genome of a diploid strain YJS329. These GSV events led to copy number variations (CNVs) in many chromosomal segments as well as one whole chromosome in the ZTW1 genome. Changes in the DNA dosage of certain functional genes directly affected their expression levels and the resultant ZTW1 phenotypes. Moreover, CNVs of large chromosomal regions triggered an aneuploidy stress in ZTW1. This stress decreased the proliferation ability and tolerance of ZTW1 to various stresses, while aneuploidy response stress may also provide some benefits to the fermentation performance of the yeast, including increased fermentation rates and decreased byproduct generation. This work reveals genomic characters of the bioethanol S. cerevisiae strain ZTW1 and suggests that GSV is an important kind of mutation that changes the traits of industrial S. cerevisiae strains. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Pathgroups, a dynamic data structure for genome reconstruction problems.

Science.gov (United States)

Zheng, Chunfang

2010-07-01

Ancestral gene order reconstruction problems, including the median problem, quartet construction, small phylogeny, guided genome halving and genome aliquoting, are NP hard. Available heuristics dedicated to each of these problems are computationally costly for even small instances. We present a data structure enabling rapid heuristic solution to all these ancestral genome reconstruction problems. A generic greedy algorithm with look-ahead based on an automatically generated priority system suffices for all the problems using this data structure. The efficiency of the algorithm is due to fast updating of the structure during run time and to the simplicity of the priority scheme. We illustrate with the first rapid algorithm for quartet construction and apply this to a set of yeast genomes to corroborate a recent gene sequence-based phylogeny. http://albuquerque.bioinformatics.uottawa.ca/pathgroup/Quartet.html chunfang313@gmail.com Supplementary data are available at Bioinformatics online.

The complete chloroplast genome sequence of Podocarpus lambertii: genome structure, evolutionary aspects, gene content and SSR detection.

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Leila do Nascimento Vieira

Full Text Available BACKGROUND: Podocarpus lambertii (Podocarpaceae is a native conifer from the Brazilian Atlantic Forest Biome, which is considered one of the 25 biodiversity hotspots in the world. The advancement of next-generation sequencing technologies has enabled the rapid acquisition of whole chloroplast (cp genome sequences at low cost. Several studies have proven the potential of cp genomes as tools to understand enigmatic and basal phylogenetic relationships at different taxonomic levels, as well as further probe the structural and functional evolution of plants. In this work, we present the complete cp genome sequence of P. lambertii. METHODOLOGY/PRINCIPAL FINDINGS: The P. lambertii cp genome is 133,734 bp in length, and similar to other sequenced cupressophytes, it lacks one of the large inverted repeat regions (IR. It contains 118 unique genes and one duplicated tRNA (trnN-GUU, which occurs as an inverted repeat sequence. The rps16 gene was not found, which was previously reported for the plastid genome of another Podocarpaceae (Nageia nagi and Araucariaceae (Agathis dammara. Structurally, P. lambertii shows 4 inversions of a large DNA fragment ∼20,000 bp compared to the Podocarpus totara cp genome. These unexpected characteristics may be attributed to geographical distance and different adaptive needs. The P. lambertii cp genome presents a total of 28 tandem repeats and 156 SSRs, with homo- and dipolymers being the most common and tri-, tetra-, penta-, and hexapolymers occurring with less frequency. CONCLUSION: The complete cp genome sequence of P. lambertii revealed significant structural changes, even in species from the same genus. These results reinforce the apparently loss of rps16 gene in Podocarpaceae cp genome. In addition, several SSRs in the P. lambertii cp genome are likely intraspecific polymorphism sites, which may allow highly sensitive phylogeographic and population structure studies, as well as phylogenetic studies of species of

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.

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

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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.

Comparative genomics analysis of rice and pineapple contributes to understand the chromosome number reduction and genomic changes in grasses

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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.

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...

Evolutionary genomics and population structure of Entamoeba histolytica

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Koushik Das

2014-11-01

Full Text Available Amoebiasis caused by the gastrointestinal parasite Entamoeba histolytica has diverse disease outcomes. Study of genome and evolution of this fascinating parasite will help us to understand the basis of its virulence and explain why, when and how it causes diseases. In this review, we have summarized current knowledge regarding evolutionary genomics of E. histolytica and discussed their association with parasite phenotypes and its differential pathogenic behavior. How genetic diversity reveals parasite population structure has also been discussed. Queries concerning their evolution and population structure which were required to be addressed have also been highlighted. This significantly large amount of genomic data will improve our knowledge about this pathogenic species of Entamoeba.

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

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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

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.

Child Development and Structural Variation in the Human Genome

Science.gov (United States)

Zhang, Ying; Haraksingh, Rajini; Grubert, Fabian; Abyzov, Alexej; Gerstein, Mark; Weissman, Sherman; Urban, Alexander E.

2013-01-01

Structural variation of the human genome sequence is the insertion, deletion, or rearrangement of stretches of DNA sequence sized from around 1,000 to millions of base pairs. Over the past few years, structural variation has been shown to be far more common in human genomes than previously thought. Very little is currently known about the effects…

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.

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

Unifying Inference of Meso-Scale Structures in Networks.

Science.gov (United States)

Tunç, Birkan; Verma, Ragini

2015-01-01

Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities) of the brain, as well as its auxiliary characteristics (core-periphery).

Unifying Inference of Meso-Scale Structures in Networks.

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Birkan Tunç

Full Text Available Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities of the brain, as well as its auxiliary characteristics (core-periphery.

Structural Genomics and Drug Discovery for Infectious Diseases

International Nuclear Information System (INIS)

Anderson, W.F.

2009-01-01

The application of structural genomics methods and approaches to proteins from organisms causing infectious diseases is making available the three dimensional structures of many proteins that are potential drug targets and laying the groundwork for structure aided drug discovery efforts. There are a number of structural genomics projects with a focus on pathogens that have been initiated worldwide. The Center for Structural Genomics of Infectious Diseases (CSGID) was recently established to apply state-of-the-art high throughput structural biology technologies to the characterization of proteins from the National Institute for Allergy and Infectious Diseases (NIAID) category A-C pathogens and organisms causing emerging, or re-emerging infectious diseases. The target selection process emphasizes potential biomedical benefits. Selected proteins include known drug targets and their homologs, essential enzymes, virulence factors and vaccine candidates. The Center also provides a structure determination service for the infectious disease scientific community. The ultimate goal is to generate a library of structures that are available to the scientific community and can serve as a starting point for further research and structure aided drug discovery for infectious diseases. To achieve this goal, the CSGID will determine protein crystal structures of 400 proteins and protein-ligand complexes using proven, rapid, highly integrated, and cost-effective methods for such determination, primarily by X-ray crystallography. High throughput crystallographic structure determination is greatly aided by frequent, convenient access to high-performance beamlines at third-generation synchrotron X-ray sources.

Multiscale modeling of three-dimensional genome

Science.gov (United States)

Zhang, Bin; Wolynes, Peter

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

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.

Structural genomics of infectious disease drug targets: the SSGCID

International Nuclear Information System (INIS)

Stacy, Robin; Begley, Darren W.; Phan, Isabelle; Staker, Bart L.; Van Voorhis, Wesley C.; Varani, Gabriele; Buchko, Garry W.; Stewart, Lance J.; Myler, Peter J.

2011-01-01

An introduction and overview of the focus, goals and overall mission of the Seattle Structural Genomics Center for Infectious Disease (SSGCID) is given. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) is a consortium of researchers at Seattle BioMed, Emerald BioStructures, the University of Washington and Pacific Northwest National Laboratory that was established to apply structural genomics approaches to drug targets from infectious disease organisms. The SSGCID is currently funded over a five-year period by the National Institute of Allergy and Infectious Diseases (NIAID) to determine the three-dimensional structures of 400 proteins from a variety of Category A, B and C pathogens. Target selection engages the infectious disease research and drug-therapy communities to identify drug targets, essential enzymes, virulence factors and vaccine candidates of biomedical relevance to combat infectious diseases. The protein-expression systems, purified proteins, ligand screens and three-dimensional structures produced by SSGCID constitute a valuable resource for drug-discovery research, all of which is made freely available to the greater scientific community. This issue of Acta Crystallographica Section F, entirely devoted to the work of the SSGCID, covers the details of the high-throughput pipeline and presents a series of structures from a broad array of pathogenic organisms. Here, a background is provided on the structural genomics of infectious disease, the essential components of the SSGCID pipeline are discussed and a survey of progress to date is presented

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.

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

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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.

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.

Genome-wide survey of single-nucleotide polymorphisms reveals fine-scale population structure and signs of selection in the threatened Caribbean elkhorn coral, Acropora palmata

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Meghann K. Devlin-Durante

2017-11-01

Full Text Available The advent of next-generation sequencing tools has made it possible to conduct fine-scale surveys of population differentiation and genome-wide scans for signatures of selection in non-model organisms. Such surveys are of particular importance in sharply declining coral species, since knowledge of population boundaries and signs of local adaptation can inform restoration and conservation efforts. Here, we use genome-wide surveys of single-nucleotide polymorphisms in the threatened Caribbean elkhorn coral, Acropora palmata, to reveal fine-scale population structure and infer the major barrier to gene flow that separates the eastern and western Caribbean populations between the Bahamas and Puerto Rico. The exact location of this break had been subject to discussion because two previous studies based on microsatellite data had come to differing conclusions. We investigate this contradiction by analyzing an extended set of 11 microsatellite markers including the five previously employed and discovered that one of the original microsatellite loci is apparently under selection. Exclusion of this locus reconciles the results from the SNP and the microsatellite datasets. Scans for outlier loci in the SNP data detected 13 candidate loci under positive selection, however there was no correlation between available environmental parameters and genetic distance. Together, these results suggest that reef restoration efforts should use local sources and utilize existing functional variation among geographic regions in ex situ crossing experiments to improve stress resistance of this species.

Genome-wide survey of single-nucleotide polymorphisms reveals fine-scale population structure and signs of selection in the threatened Caribbean elkhorn coral, Acropora palmata.

Science.gov (United States)

Devlin-Durante, Meghann K; Baums, Iliana B

2017-01-01

The advent of next-generation sequencing tools has made it possible to conduct fine-scale surveys of population differentiation and genome-wide scans for signatures of selection in non-model organisms. Such surveys are of particular importance in sharply declining coral species, since knowledge of population boundaries and signs of local adaptation can inform restoration and conservation efforts. Here, we use genome-wide surveys of single-nucleotide polymorphisms in the threatened Caribbean elkhorn coral, Acropora palmata , to reveal fine-scale population structure and infer the major barrier to gene flow that separates the eastern and western Caribbean populations between the Bahamas and Puerto Rico. The exact location of this break had been subject to discussion because two previous studies based on microsatellite data had come to differing conclusions. We investigate this contradiction by analyzing an extended set of 11 microsatellite markers including the five previously employed and discovered that one of the original microsatellite loci is apparently under selection. Exclusion of this locus reconciles the results from the SNP and the microsatellite datasets. Scans for outlier loci in the SNP data detected 13 candidate loci under positive selection, however there was no correlation between available environmental parameters and genetic distance. Together, these results suggest that reef restoration efforts should use local sources and utilize existing functional variation among geographic regions in ex situ crossing experiments to improve stress resistance of this species.

Structural biology at York Structural Biology Laboratory; laboratory information management systems for structural genomics

Czech Academy of Sciences Publication Activity Database

Dohnálek, Jan

2005-01-01

Roč. 12, č. 1 (2005), s. 3 ISSN 1211-5894. [Meeting of Structural Biologists /4./. 10.03.2005-12.03.2005, Nové Hrady] R&D Projects: GA MŠk(CZ) 1K05008 Keywords : structural biology * LIMS * structural genomics Subject RIV: CD - Macromolecular Chemistry

Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

2007-09-02

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

From structure prediction to genomic screens for novel non-coding RNAs

DEFF Research Database (Denmark)

Gorodkin, Jan; Hofacker, Ivo L.

2011-01-01

Abstract: Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction....... This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early...... upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other....

Human Genome Sequencing in Health and Disease

Science.gov (United States)

Gonzaga-Jauregui, Claudia; Lupski, James R.; Gibbs, Richard A.

2013-01-01

Following the “finished,” euchromatic, haploid human reference genome sequence, the rapid development of novel, faster, and cheaper sequencing technologies is making possible the era of personalized human genomics. Personal diploid human genome sequences have been generated, and each has contributed to our better understanding of variation in the human genome. We have consequently begun to appreciate the vastness of individual genetic variation from single nucleotide to structural variants. Translation of genome-scale variation into medically useful information is, however, in its infancy. This review summarizes the initial steps undertaken in clinical implementation of personal genome information, and describes the application of whole-genome and exome sequencing to identify the cause of genetic diseases and to suggest adjuvant therapies. Better analysis tools and a deeper understanding of the biology of our genome are necessary in order to decipher, interpret, and optimize clinical utility of what the variation in the human genome can teach us. Personal genome sequencing may eventually become an instrument of common medical practice, providing information that assists in the formulation of a differential diagnosis. We outline herein some of the remaining challenges. PMID:22248320

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.

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

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

High-Temperature Structural Analysis of a Small-Scale Prototype of a Process Heat Exchanger (IV) - Macroscopic High-Temperature Elastic-Plastic Analysis -

International Nuclear Information System (INIS)

Song, Kee Nam; Hong, Sung Deok; Park, Hong Yoon

2011-01-01

A PHE (Process Heat Exchanger) is a key component required to transfer heat energy of 950 .deg. C generated in a VHTR (Very High Temperature Reactor) to a chemical reaction that yields a large quantity of hydrogen. A small-scale PHE prototype made of Hastelloy-X was scheduled for testing in a small-scale gas loop at the Korea Atomic Energy Research Institute. In this study, as a part of the evaluation of the high-temperature structural integrity of the PHE prototype, high-temperature structural analysis modeling, and macroscopic thermal and elastic-plastic structural analysis of the PHE prototype were carried out under the gas-loop test conditions as a preliminary qwer123$ study before carrying out the performance test in the gas loop. The results obtained in this study will be used to design the performance test setup for the modified PHE prototype

Structured RNAs and synteny regions in the pig genome

DEFF Research Database (Denmark)

Anthon, Christian; Tafer, Hakim; Havgaard, Jakob H

2014-01-01

BACKGROUND: Annotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However......, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals. RESULTS: We present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure...... lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome...

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.

A multivalent adsorption apparatus explains the broad host range of phage phi92: a comprehensive genomic and structural analysis.

Science.gov (United States)

Schwarzer, David; Buettner, Falk F R; Browning, Christopher; Nazarov, Sergey; Rabsch, Wolfgang; Bethe, Andrea; Oberbeck, Astrid; Bowman, Valorie D; Stummeyer, Katharina; Mühlenhoff, Martina; Leiman, Petr G; Gerardy-Schahn, Rita

2012-10-01

Bacteriophage phi92 is a large, lytic myovirus isolated in 1983 from pathogenic Escherichia coli strains that carry a polysialic acid capsule. Here we report the genome organization of phi92, the cryoelectron microscopy reconstruction of its virion, and the reinvestigation of its host specificity. The genome consists of a linear, double-stranded 148,612-bp DNA sequence containing 248 potential open reading frames and 11 putative tRNA genes. Orthologs were found for 130 of the predicted proteins. Most of the virion proteins showed significant sequence similarities to proteins of myoviruses rv5 and PVP-SE1, indicating that phi92 is a new member of the novel genus of rv5-like phages. Reinvestigation of phi92 host specificity showed that the host range is not limited to polysialic acid-encapsulated Escherichia coli but includes most laboratory strains of Escherichia coli and many Salmonella strains. Structure analysis of the phi92 virion demonstrated the presence of four different types of tail fibers and/or tailspikes, which enable the phage to use attachment sites on encapsulated and nonencapsulated bacteria. With this report, we provide the first detailed description of a multivalent, multispecies phage armed with a host cell adsorption apparatus resembling a nanosized Swiss army knife. The genome, structure, and, in particular, the organization of the baseplate of phi92 demonstrate how a bacteriophage can evolve into a multi-pathogen-killing agent.

Long-Range Order and Fractality in the Structure and Organization of Eukaryotic Genomes

Science.gov (United States)

Polychronopoulos, Dimitris; Tsiagkas, Giannis; Athanasopoulou, Labrini; Sellis, Diamantis; Almirantis, Yannis

2014-12-01

The late Professor J.S. Nicolis always emphasized, both in his writings and in presentations and discussions with students and friends, the relevance of a dynamical systems approach to biology. In particular, viewing the genome as a "biological text" captures the dynamical character of both the evolution and function of the organisms in the form of correlations indicating the presence of a long-range order. This genomic structure can be expressed in forms reminiscent of natural languages and several temporal and spatial traces l by the functioning of dynamical systems: Zipf laws, self-similarity and fractality. Here we review several works of our group and recent unpublished results, focusing on the chromosomal distribution of biologically active genomic components: Genes and protein-coding segments, CpG islands, transposable elements belonging to all major classes and several types of conserved non-coding genomic elements. We report the systematic appearance of power-laws in the size distribution of the distances between elements belonging to each of these types of functional genomic elements. Moreover, fractality is also found in several cases, using box-counting and entropic scaling.We present here, for the first time in a unified way, an aggregative model of the genomic dynamics which can explain the observed patterns on the grounds of known phenomena accompanying genome evolution. Our results comply with recent findings about a "fractal globule" geometry of chromatin in the eukaryotic nucleus.

Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly

DEFF Research Database (Denmark)

Li, Yingrui; Zheng, Hancheng; Luo, Ruibang

2011-01-01

Here we use whole-genome de novo assembly of second-generation sequencing reads to map structural variation (SV) in an Asian genome and an African genome. Our approach identifies small- and intermediate-size homozygous variants (1-50 kb) including insertions, deletions, inversions and their precise...

Genetic Characterization and Comparative Genome Analysis of Brucella melitensis Isolates from India

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Sarwar Azam

2016-01-01

Full Text Available Brucellosis is the most frequent zoonotic disease worldwide, with over 500,000 new human infections every year. Brucella melitensis, the most virulent species in humans, primarily affects goats and the zoonotic transmission occurs by ingestion of unpasteurized milk products or through direct contact with fetal tissues. Brucellosis is endemic in India but no information is available on population structure and genetic diversity of Brucella spp. in India. We performed multilocus sequence typing of four B. melitensis strains isolated from naturally infected goats from India. For more detailed genetic characterization, we carried out whole genome sequencing and comparative genome analysis of one of the B. melitensis isolates, Bm IND1. Genome analysis identified 141 unique SNPs, 78 VNTRs, 51 Indels, and 2 putative prophage integrations in the Bm IND1 genome. Our data may help to develop improved epidemiological typing tools and efficient preventive strategies to control brucellosis.

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…

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

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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

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.

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

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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.

The complete chloroplast genome sequence of an endemic monotypic genus Hagenia (Rosaceae: structural comparative analysis, gene content and microsatellite detection

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Andrew W. Gichira

2017-01-01

Full Text Available Hagenia is an endangered monotypic genus endemic to the topical mountains of Africa. The only species, Hagenia abyssinica (Bruce J.F. Gmel, is an important medicinal plant producing bioactive compounds that have been traditionally used by African communities as a remedy for gastrointestinal ailments in both humans and animals. Complete chloroplast genomes have been applied in resolving phylogenetic relationships within plant families. We employed high-throughput sequencing technologies to determine the complete chloroplast genome sequence of H. abyssinica. The genome is a circular molecule of 154,961 base pairs (bp, with a pair of Inverted Repeats (IR 25,971 bp each, separated by two single copies; a large (LSC, 84,320 bp and a small single copy (SSC, 18,696. H. abyssinica’s chloroplast genome has a 37.1% GC content and encodes 112 unique genes, 78 of which code for proteins, 30 are tRNA genes and four are rRNA genes. A comparative analysis with twenty other species, sequenced to-date from the family Rosaceae, revealed similarities in structural organization, gene content and arrangement. The observed size differences are attributed to the contraction/expansion of the inverted repeats. The translational initiation factor gene (infA which had been previously reported in other chloroplast genomes was conspicuously missing in H. abyssinica. A total of 172 microsatellites and 49 large repeat sequences were detected in the chloroplast genome. A Maximum Likelihood analyses of 71 protein-coding genes placed Hagenia in Rosoideae. The availability of a complete chloroplast genome, the first in the Sanguisorbeae tribe, is beneficial for further molecular studies on taxonomic and phylogenomic resolution within the Rosaceae family.

The complete chloroplast genome sequence of an endemic monotypic genus Hagenia (Rosaceae): structural comparative analysis, gene content and microsatellite detection.

Science.gov (United States)

Gichira, Andrew W; Li, Zhizhong; Saina, Josphat K; Long, Zhicheng; Hu, Guangwan; Gituru, Robert W; Wang, Qingfeng; Chen, Jinming

2017-01-01

Hagenia is an endangered monotypic genus endemic to the topical mountains of Africa. The only species, Hagenia abyssinica (Bruce) J.F. Gmel, is an important medicinal plant producing bioactive compounds that have been traditionally used by African communities as a remedy for gastrointestinal ailments in both humans and animals. Complete chloroplast genomes have been applied in resolving phylogenetic relationships within plant families. We employed high-throughput sequencing technologies to determine the complete chloroplast genome sequence of H. abyssinica. The genome is a circular molecule of 154,961 base pairs (bp), with a pair of Inverted Repeats (IR) 25,971 bp each, separated by two single copies; a large (LSC, 84,320 bp) and a small single copy (SSC, 18,696). H. abyssinica 's chloroplast genome has a 37.1% GC content and encodes 112 unique genes, 78 of which code for proteins, 30 are tRNA genes and four are rRNA genes. A comparative analysis with twenty other species, sequenced to-date from the family Rosaceae, revealed similarities in structural organization, gene content and arrangement. The observed size differences are attributed to the contraction/expansion of the inverted repeats. The translational initiation factor gene ( infA ) which had been previously reported in other chloroplast genomes was conspicuously missing in H. abyssinica . A total of 172 microsatellites and 49 large repeat sequences were detected in the chloroplast genome. A Maximum Likelihood analyses of 71 protein-coding genes placed Hagenia in Rosoideae. The availability of a complete chloroplast genome, the first in the Sanguisorbeae tribe, is beneficial for further molecular studies on taxonomic and phylogenomic resolution within the Rosaceae family.

Genome-wide analysis of the WRKY transcription factors in aegilops tauschii.

Science.gov (United States)

Ma, Jianhui; Zhang, Daijing; Shao, Yun; Liu, Pei; Jiang, Lina; Li, Chunxi

2014-01-01

The WRKY transcription factors (TFs) play important roles in responding to abiotic and biotic stress in plants. However, due to its unfinished genome sequencing, relatively few WRKY TFs with full-length coding sequences (CDSs) have been identified in wheat. Instead, the Aegilops tauschii genome, which is the D-genome progenitor of the hexaploid wheat genome, provides important resources for the discovery of new genes. In this study, we performed a bioinformatics analysis to identify WRKY TFs with full-length CDSs from the A. tauschii genome. A detailed evolutionary analysis for all these TFs was conducted, and quantitative real-time PCR was carried out to investigate the expression patterns of the abiotic stress-related WRKY TFs under different abiotic stress conditions in A. tauschii seedlings. A total of 93 WRKY TFs were identified from A. tauschii, and 79 of them were found to be newly discovered genes compared with wheat. Gene phylogeny, gene structure and chromosome location of the 93 WRKY TFs were fully analyzed. These studies provide a global view of the WRKY TFs from A. tauschii and a firm foundation for further investigations in both A. tauschii and wheat. © 2015 S. Karger AG, Basel.

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.

DNA is structured as a linear "jigsaw puzzle" in the genomes of Arabidopsis, rice, and budding yeast.

Science.gov (United States)

Liu, Yun-Hua; Zhang, Meiping; Wu, Chengcang; Huang, James J; Zhang, Hong-Bin

2014-01-01

Knowledge of how a genome is structured and organized from its constituent elements is crucial to understanding its biology and evolution. Here, we report the genome structuring and organization pattern as revealed by systems analysis of the sequences of three model species, Arabidopsis, rice and yeast, at the whole-genome and chromosome levels. We found that all fundamental function elements (FFE) constituting the genomes, including genes (GEN), DNA transposable elements (DTE), retrotransposable elements (RTE), simple sequence repeats (SSR), and (or) low complexity repeats (LCR), are structured in a nonrandom and correlative manner, thus leading to a hypothesis that the DNA of the species is structured as a linear "jigsaw puzzle". Furthermore, we showed that different FFE differ in their importance in the formation and evolution of the DNA jigsaw puzzle structure between species. DTE and RTE play more important roles than GEN, LCR, and SSR in Arabidopsis, whereas GEN and RTE play more important roles than LCR, SSR, and DTE in rice. The genes having multiple recognized functions play more important roles than those having single functions. These results provide useful knowledge necessary for better understanding genome biology and evolution of the species and for effective molecular breeding of rice.

Epigenomic annotation-based interpretation of genomic data: from enrichment analysis to machine learning.

Science.gov (United States)

Dozmorov, Mikhail G

2017-10-15

One of the goals of functional genomics is to understand the regulatory implications of experimentally obtained genomic regions of interest (ROIs). Most sequencing technologies now generate ROIs distributed across the whole genome. The interpretation of these genome-wide ROIs represents a challenge as the majority of them lie outside of functionally well-defined protein coding regions. Recent efforts by the members of the International Human Epigenome Consortium have generated volumes of functional/regulatory data (reference epigenomic datasets), effectively annotating the genome with epigenomic properties. Consequently, a wide variety of computational tools has been developed utilizing these epigenomic datasets for the interpretation of genomic data. The purpose of this review is to provide a structured overview of practical solutions for the interpretation of ROIs with the help of epigenomic data. Starting with epigenomic enrichment analysis, we discuss leading tools and machine learning methods utilizing epigenomic and 3D genome structure data. The hierarchy of tools and methods reviewed here presents a practical guide for the interpretation of genome-wide ROIs within an epigenomic context. mikhail.dozmorov@vcuhealth.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Comparative Genome Structure, Secondary Metabolite, and Effector Coding Capacity across Cochliobolus Pathogens

Energy Technology Data Exchange (ETDEWEB)

Condon, Bradford J.; Leng, Yueqiang; Wu, Dongliang; Bushley, Kathryn E.; Ohm, Robin A.; Otillar, Robert; Martin, Joel; Schackwitz, Wendy; Grimwood, Jane; MohdZainudin, NurAinlzzati; Xue, Chunsheng; Wang, Rui; Manning, Viola A.; Dhillon, Braham; Tu, Zheng Jin; Steffenson, Brian J.; Salamov, Asaf; Sun, Hui; Lowry, Steve; LaButti, Kurt; Han, James; Copeland, Alex; Lindquist, Erika; Barry, Kerrie; Schmutz, Jeremy; Baker, Scott E.; Ciuffetti, Lynda M.; Grigoriev, Igor V.; Zhong, Shaobin; Turgeon, B. Gillian

2013-01-24

The genomes of five Cochliobolus heterostrophus strains, two Cochliobolus sativus strains, three additional Cochliobolus species (Cochliobolus victoriae, Cochliobolus carbonum, Cochliobolus miyabeanus), and closely related Setosphaeria turcica were sequenced at the Joint Genome Institute (JGI). The datasets were used to identify SNPs between strains and species, unique genomic regions, core secondary metabolism genes, and small secreted protein (SSP) candidate effector encoding genes with a view towards pinpointing structural elements and gene content associated with specificity of these closely related fungi to different cereal hosts. Whole-genome alignment shows that three to five of each genome differs between strains of the same species, while a quarter of each genome differs between species. On average, SNP counts among field isolates of the same C. heterostrophus species are more than 25 higher than those between inbred lines and 50 lower than SNPs between Cochliobolus species. The suites of nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and SSP encoding genes are astoundingly diverse among species but remarkably conserved among isolates of the same species, whether inbred or field strains, except for defining examples that map to unique genomic regions. Functional analysis of several strain-unique PKSs and NRPSs reveal a strong correlation with a role in virulence.

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

Analysis of pan-genome content and its application in microbial identification

DEFF Research Database (Denmark)

Lukjancenko, Oksana

microorganisms and eventually speed up the diagnosis of foodborne illnesses. This genomic data can give biologists many possibilities to improve knowledge of organismal evolution and complex genetic systems. The general interest of this PhD thesis is how to obtain relevant information from growing amounts...... groups or genomic structures; and to use the information of a specific proteome to predict which species it might belong to. Two different algorithms, BLAST and profile Hidden Markov Models (HMMs), are used to determine similarity between sequences and to address the questions in this thesis. The first...... the application of PanFunPro to a set of more than 2000 genomes; this paper aims to define set of protein families, which are conserved among all the genomes. Papers V demonstrates comparative genomics analysis of proteomes, belonging to Vibrio genus. In the last project, described in Chapter 5, both BLAST...

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

Science.gov (United States)

Lewis, Tony E; Sillitoe, Ian; Andreeva, Antonina; Blundell, Tom L; Buchan, Daniel W A; Chothia, Cyrus; Cuff, Alison; Dana, Jose M; Filippis, Ioannis; Gough, Julian; Hunter, Sarah; Jones, David T; Kelley, Lawrence A; Kleywegt, Gerard J; Minneci, Federico; Mitchell, Alex; Murzin, Alexey G; Ochoa-Montaño, Bernardo; Rackham, Owen J L; Smith, James; Sternberg, Michael J E; Velankar, Sameer; Yeats, Corin; Orengo, Christine

2013-01-01

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

Statistical properties of thermodynamically predicted RNA secondary structures in viral genomes

Science.gov (United States)

Spanò, M.; Lillo, F.; Miccichè, S.; Mantegna, R. N.

2008-10-01

By performing a comprehensive study on 1832 segments of 1212 complete genomes of viruses, we show that in viral genomes the hairpin structures of thermodynamically predicted RNA secondary structures are more abundant than expected under a simple random null hypothesis. The detected hairpin structures of RNA secondary structures are present both in coding and in noncoding regions for the four groups of viruses categorized as dsDNA, dsRNA, ssDNA and ssRNA. For all groups, hairpin structures of RNA secondary structures are detected more frequently than expected for a random null hypothesis in noncoding rather than in coding regions. However, potential RNA secondary structures are also present in coding regions of dsDNA group. In fact, we detect evolutionary conserved RNA secondary structures in conserved coding and noncoding regions of a large set of complete genomes of dsDNA herpesviruses.

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.

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

The scale of population structure in Arabidopsis thaliana.

Directory of Open Access Journals (Sweden)

Alexander Platt

2010-02-01

Full Text Available The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales.

High-Temperature Structural Analysis of a Small-Scale PHE Prototype under the Test Condition of a Small-Scale Gas Loop

International Nuclear Information System (INIS)

Song, K.; Hong, S.; Park, H.

2012-01-01

A process heat exchanger (PHE) is a key component for transferring the high-temperature heat generated from a very high-temperature reactor (VHTR) to a chemical reaction for the massive production of hydrogen. The Korea Atomic Energy Research Institute has designed and assembled a small-scale nitrogen gas loop for a performance test on VHTR components and has manufactured a small-scale PHE prototype made of Hastelloy-X alloy. A performance test on the PHE prototype is underway in the gas loop, where different kinds of pipelines connecting to the PHE prototype are tested for reducing the thermal stress under the expansion of the PHE prototype. In this study, to evaluate the high-temperature structural integrity of the PHE prototype under the test condition of the gas loop, a realistic and effective boundary condition imposing the stiffness of the pipelines connected to the PHE prototype was suggested. An equivalent spring stiffness to reduce the thermal stress under the expansion of the PHE prototype was computed from the bending deformation and expansion of the pipelines connected to the PHE. A structural analysis on the PHE prototype was also carried out by imposing the suggested boundary condition. As a result of the analysis, the structural integrity of the PHE prototype seems to be maintained under the test condition of the gas loop.

Population genomic structure and linkage disequilibrium analysis of South African goat breeds using genome-wide SNP data.

Science.gov (United States)

Mdladla, K; Dzomba, E F; Huson, H J; Muchadeyi, F C

2016-08-01

The sustainability of goat farming in marginal areas of southern Africa depends on local breeds that are adapted to specific agro-ecological conditions. Unimproved non-descript goats are the main genetic resources used for the development of commercial meat-type breeds of South Africa. Little is known about genetic diversity and the genetics of adaptation of these indigenous goat populations. This study investigated the genetic diversity, population structure and breed relations, linkage disequilibrium, effective population size and persistence of gametic phase in goat populations of South Africa. Three locally developed meat-type breeds of the Boer (n = 33), Savanna (n = 31), Kalahari Red (n = 40), a feral breed of Tankwa (n = 25) and unimproved non-descript village ecotypes (n = 110) from four goat-producing provinces of the Eastern Cape, KwaZulu-Natal, Limpopo and North West were assessed using the Illumina Goat 50K SNP Bead Chip assay. The proportion of SNPs with minor allele frequencies >0.05 ranged from 84.22% in the Tankwa to 97.58% in the Xhosa ecotype, with a mean of 0.32 ± 0.13 across populations. Principal components analysis, admixture and pairwise FST identified Tankwa as a genetically distinct population and supported clustering of the populations according to their historical origins. Genome-wide FST identified 101 markers potentially under positive selection in the Tankwa. Average linkage disequilibrium was highest in the Tankwa (r(2)  = 0.25 ± 0.26) and lowest in the village ecotypes (r(2) range = 0.09 ± 0.12 to 0.11 ± 0.14). We observed an effective population size of 100 kb with the exception of those in Savanna and Tswana populations. This study highlights the high level of genetic diversity in South African indigenous goats as well as the utility of the genome-wide SNP marker panels in genetic studies of these populations. © 2016 Stichting International Foundation for Animal Genetics.

Hierarchical structure and cytocompatibility of fish scales from Carassius auratus

International Nuclear Information System (INIS)

Fang, Zhou; Wang, Yukun; Feng, Qingling; Kienzle, Arne; Müller, Werner E.G.

2014-01-01

To study the structure and the cytocompatibility of fish scales from Carassius auratus, scanning electron microscopy (SEM) was used to observe the morphology of fish scales treated with different processing methods. Based on varying morphologies and components, the fish scales can be divided into three regions on the surface and three layers in vertical. The functions of these three individual layers were analyzed. SEM results show that the primary inorganic components are spherical or cubic hydroxyapatite (HA) nanoparticles. The fish scales have an ∼ 60° overlapped plywood structure of lamellas in the fibrillary plate. The plywood structure consists of co-aligned type I collagen fibers, which are parallel to the HA lamellas. X-ray diffraction (XRD), thermogravimetric analysis/differential scanning calorimetry (TGA/DSC) and Fourier transform infrared (FTIR) analysis indicate that the main components are HA and type I collagen fibers. MC3T3-E1 cell culture results show a high cytocompatibility and the ability to guide cell proliferation and migration along the scale ridge channels of the fish scales. This plywood structure provides inspiration for a structure-enhanced composite material. - Highlights: • The Carassius auratus fish scale can be divided into 3 layers rather than 2. • The functions of these three individual layers were firstly analyzed. • The fish scale shows a high cytocompatibility. • The fish scale can guide cells migration along the scale ridge channels

Hierarchical structure and cytocompatibility of fish scales from Carassius auratus

Energy Technology Data Exchange (ETDEWEB)

Fang, Zhou [State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Wang, Yukun [State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Beijing 100084 (China); Feng, Qingling, E-mail: biomater@mail.tsinghua.edu.cn [State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Key Laboratory of Advanced Materials of Ministry of Education of China, School of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Kienzle, Arne; Müller, Werner E.G. [Institut für Physiologische Chemie, Abteilung Angewandte Molekularbiologie, Johannes Gutenberg-Universität, Duesbergweg 6, Mainz 55099 (Germany)

2014-10-01

To study the structure and the cytocompatibility of fish scales from Carassius auratus, scanning electron microscopy (SEM) was used to observe the morphology of fish scales treated with different processing methods. Based on varying morphologies and components, the fish scales can be divided into three regions on the surface and three layers in vertical. The functions of these three individual layers were analyzed. SEM results show that the primary inorganic components are spherical or cubic hydroxyapatite (HA) nanoparticles. The fish scales have an ∼ 60° overlapped plywood structure of lamellas in the fibrillary plate. The plywood structure consists of co-aligned type I collagen fibers, which are parallel to the HA lamellas. X-ray diffraction (XRD), thermogravimetric analysis/differential scanning calorimetry (TGA/DSC) and Fourier transform infrared (FTIR) analysis indicate that the main components are HA and type I collagen fibers. MC3T3-E1 cell culture results show a high cytocompatibility and the ability to guide cell proliferation and migration along the scale ridge channels of the fish scales. This plywood structure provides inspiration for a structure-enhanced composite material. - Highlights: • The Carassius auratus fish scale can be divided into 3 layers rather than 2. • The functions of these three individual layers were firstly analyzed. • The fish scale shows a high cytocompatibility. • The fish scale can guide cells migration along the scale ridge channels.

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....

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

Complete Chloroplast Genome of the Wollemi Pine (Wollemia nobilis): Structure and Evolution.

Science.gov (United States)

Yap, Jia-Yee S; Rohner, Thore; Greenfield, Abigail; Van Der Merwe, Marlien; McPherson, Hannah; Glenn, Wendy; Kornfeld, Geoff; Marendy, Elessa; Pan, Annie Y H; Wilton, Alan; Wilkins, Marc R; Rossetto, Maurizio; Delaney, Sven K

2015-01-01

The Wollemi pine (Wollemia nobilis) is a rare Southern conifer with striking morphological similarity to fossil pines. A small population of W. nobilis was discovered in 1994 in a remote canyon system in the Wollemi National Park (near Sydney, Australia). This population contains fewer than 100 individuals and is critically endangered. Previous genetic studies of the Wollemi pine have investigated its evolutionary relationship with other pines in the family Araucariaceae, and have suggested that the Wollemi pine genome contains little or no variation. However, these studies were performed prior to the widespread use of genome sequencing, and their conclusions were based on a limited fraction of the Wollemi pine genome. In this study, we address this problem by determining the entire sequence of the W. nobilis chloroplast genome. A detailed analysis of the structure of the genome is presented, and the evolution of the genome is inferred by comparison with the chloroplast sequences of other members of the Araucariaceae and the related family Podocarpaceae. Pairwise alignments of whole genome sequences, and the presence of unique pseudogenes, gene duplications and insertions in W. nobilis and Araucariaceae, indicate that the W. nobilis chloroplast genome is most similar to that of its sister taxon Agathis. However, the W. nobilis genome contains an unusually high number of repetitive sequences, and these could be used in future studies to investigate and conserve any remnant genetic diversity in the Wollemi pine.

Population Structure and Genomic Breed Composition in an Angus-Brahman Crossbred Cattle Population.

Science.gov (United States)

Gobena, Mesfin; Elzo, Mauricio A; Mateescu, Raluca G

2018-01-01

Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage-indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due

Population Structure and Genomic Breed Composition in an Angus–Brahman Crossbred Cattle Population

Directory of Open Access Journals (Sweden)

Mesfin Gobena

2018-03-01

Full Text Available Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals

Chemical biology on the genome.

Science.gov (United States)

Balasubramanian, Shankar

2014-08-15

In this article I discuss studies towards understanding the structure and function of DNA in the context of genomes from the perspective of a chemist. The first area I describe concerns the studies that led to the invention and subsequent development of a method for sequencing DNA on a genome scale at high speed and low cost, now known as Solexa/Illumina sequencing. The second theme will feature the four-stranded DNA structure known as a G-quadruplex with a focus on its fundamental properties, its presence in cellular genomic DNA and the prospects for targeting such a structure in cels with small molecules. The final topic for discussion is naturally occurring chemically modified DNA bases with an emphasis on chemistry for decoding (or sequencing) such modifications in genomic DNA. The genome is a fruitful topic to be further elucidated by the creation and application of chemical approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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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.

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.

Barcode server: a visualization-based genome analysis system.

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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.

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

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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.

Genome-wide comparative analysis reveals similar types of NBS genes in hybrid Citrus sinensis genome and original Citrus clementine genome and provides new insights into non-TIR NBS genes.

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Yunsheng Wang

Full Text Available In this study, we identified and compared nucleotide-binding site (NBS domain-containing genes from three Citrus genomes (C. clementina, C. sinensis from USA and C. sinensis from China. Phylogenetic analysis of all Citrus NBS genes across these three genomes revealed that there are three approximately evenly numbered groups: one group contains the Toll-Interleukin receptor (TIR domain and two different Non-TIR groups in which most of proteins contain the Coiled Coil (CC domain. Motif analysis confirmed that the two groups of CC-containing NBS genes are from different evolutionary origins. We partitioned NBS genes into clades using NBS domain sequence distances and found most clades include NBS genes from all three Citrus genomes. This suggests that three Citrus genomes have similar numbers and types of NBS genes. We also mapped the re-sequenced reads of three pomelo and three mandarin genomes onto the C. sinensis genome. We found that most NBS genes of the hybrid C. sinensis genome have corresponding homologous genes in both pomelo and mandarin genomes. The homologous NBS genes in pomelo and mandarin suggest that the parental species of C. sinensis may contain similar types of NBS genes. This explains why the hybrid C. sinensis and original C. clementina have similar types of NBS genes in this study. Furthermore, we found that sequence variation amongst Citrus NBS genes were shaped by multiple independent and shared accelerated mutation accumulation events among different groups of NBS genes and in different Citrus genomes. Our comparative analyses yield valuable insight into the structure, organization and evolution of NBS genes in Citrus genomes. Furthermore, our comprehensive analysis showed that the non-TIR NBS genes can be divided into two groups that come from different evolutionary origins. This provides new insights into non-TIR genes, which have not received much attention.

Scale modeling of reinforced concrete structures subjected to seismic loading

International Nuclear Information System (INIS)

Dove, R.C.

1983-01-01

Reinforced concrete, Category I structures are so large that the possibility of seismicly testing the prototype structures under controlled conditions is essentially nonexistent. However, experimental data, from which important structural properties can be determined and existing and new methods of seismic analysis benchmarked, are badly needed. As a result, seismic experiments on scaled models are of considerable interest. In this paper, the scaling laws are developed in some detail so that assumptions and choices based on judgement can be clearly recognized and their effects discussed. The scaling laws developed are then used to design a reinforced concrete model of a Category I structure. Finally, how scaling is effected by various types of damping (viscous, structural, and Coulomb) is discussed

Structural and sequence diversity of the transposon Galileo in the Drosophila willistoni genome.

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Gonçalves, Juliana W; Valiati, Victor Hugo; Delprat, Alejandra; Valente, Vera L S; Ruiz, Alfredo

2014-09-13

Galileo is one of three members of the P superfamily of DNA transposons. It was originally discovered in Drosophila buzzatii, in which three segregating chromosomal inversions were shown to have been generated by ectopic recombination between Galileo copies. Subsequently, Galileo was identified in six of 12 sequenced Drosophila genomes, indicating its widespread distribution within this genus. Galileo is strikingly abundant in Drosophila willistoni, a neotropical species that is highly polymorphic for chromosomal inversions, suggesting a role for this transposon in the evolution of its genome. We carried out a detailed characterization of all Galileo copies present in the D. willistoni genome. A total of 191 copies, including 133 with two terminal inverted repeats (TIRs), were classified according to structure in six groups. The TIRs exhibited remarkable variation in their length and structure compared to the most complete copy. Three copies showed extended TIRs due to internal tandem repeats, the insertion of other transposable elements (TEs), or the incorporation of non-TIR sequences into the TIRs. Phylogenetic analyses of the transposase (TPase)-encoding and TIR segments yielded two divergent clades, which we termed Galileo subfamilies V and W. Target-site duplications (TSDs) in D. willistoni Galileo copies were 7- or 8-bp in length, with the consensus sequence GTATTAC. Analysis of the region around the TSDs revealed a target site motif (TSM) with a 15-bp palindrome that may give rise to a stem-loop secondary structure. There is a remarkable abundance and diversity of Galileo copies in the D. willistoni genome, although no functional copies were found. The TIRs in particular have a dynamic structure and extend in different ways, but their ends (required for transposition) are more conserved than the rest of the element. The D. willistoni genome harbors two Galileo subfamilies (V and W) that diverged ~9 million years ago and may have descended from an ancestral

Dirofilaria immitis JYD-34 isolate: whole genome analysis

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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

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

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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.

Comparative genome analysis of Bacillus cereus group genomes withBacillus subtilis

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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.

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.

INVESTIGATING THE FACTOR STRUCTURE OF THE BLOG ATTITUDE SCALE

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Zahra SHAHSAVAR

2010-10-01

Full Text Available Due to the wide application of advanced technology in education, many attitude scales have been developed to evaluate learners’ attitudes toward educational tools. However, with the rapid development of emerging technologies, using blogs as one of the Web 2.0 tools is still in its infancy and few blog attitude scales have been developed yet. In view of this need, a lot of researchers like to design a new scale based on their conceptual and theoretical framework of their own study rather than using available scales. The present study reports the design and development of a blog attitude scale (BAS. The researchers developed a pool of items to capture the complexity of the blog attitude trait, selected 29 items in the content analysis, and assigned the scale comprising 29 items to 216 undergraduate students to explore the underlying structure of the BAS. In exploratory factor analysis, three factors were discovered: blog anxiety, blog desirability, and blog self-efficacy; 14 items were excluded. The extracted items were subjected to a confirmatory factor analysis which lent further support to the BAS underpinning structure.

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.

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

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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.

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

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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.

Harnessing Whole Genome Sequencing in Medical Mycology.

Science.gov (United States)

Cuomo, Christina A

2017-01-01

Comparative genome sequencing studies of human fungal pathogens enable identification of genes and variants associated with virulence and drug resistance. This review describes current approaches, resources, and advances in applying whole genome sequencing to study clinically important fungal pathogens. Genomes for some important fungal pathogens were only recently assembled, revealing gene family expansions in many species and extreme gene loss in one obligate species. The scale and scope of species sequenced is rapidly expanding, leveraging technological advances to assemble and annotate genomes with higher precision. By using iteratively improved reference assemblies or those generated de novo for new species, recent studies have compared the sequence of isolates representing populations or clinical cohorts. Whole genome approaches provide the resolution necessary for comparison of closely related isolates, for example, in the analysis of outbreaks or sampled across time within a single host. Genomic analysis of fungal pathogens has enabled both basic research and diagnostic studies. The increased scale of sequencing can be applied across populations, and new metagenomic methods allow direct analysis of complex samples.

Genome-wide analysis of Tol2 transposon reintegration in zebrafish

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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.

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

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

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Teo, Audrey S M; Verzotto, Davide; Yao, Fei; Nagarajan, Niranjan; Hillmer, Axel M

2015-01-01

Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.

Fast identification of folded human protein domains expressed in E. coli suitable for structural analysis

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Schlegel Brigitte

2004-03-01

Full Text Available Abstract Background High-throughput protein structure analysis of individual protein domains requires analysis of large numbers of expression clones to identify suitable constructs for structure determination. For this purpose, methods need to be implemented for fast and reliable screening of the expressed proteins as early as possible in the overall process from cloning to structure determination. Results 88 different E. coli expression constructs for 17 human protein domains were analysed using high-throughput cloning, purification and folding analysis to obtain candidates suitable for structural analysis. After 96 deep-well microplate expression and automated protein purification, protein domains were directly analysed using 1D 1H-NMR spectroscopy. In addition, analytical hydrophobic interaction chromatography (HIC was used to detect natively folded protein. With these two analytical methods, six constructs (representing two domains were quickly identified as being well folded and suitable for structural analysis. Conclusion The described approach facilitates high-throughput structural analysis. Clones expressing natively folded proteins suitable for NMR structure determination were quickly identified upon small scale expression screening using 1D 1H-NMR and/or analytical HIC. This procedure is especially effective as a fast and inexpensive screen for the 'low hanging fruits' in structural genomics.

Mutational analysis of the genome-linked protein of cowpea mosaic virus

NARCIS (Netherlands)

Carette, J.E.; Kujawa, A.; Gühl, K.; Verver, J.; Wellink, J.; Kammen, van A.

2001-01-01

In this study we have performed a mutational analysis of the cowpea mosaic comovirus (CPMV) genome-linked protein VPg to discern the structural requirements necessary for proper functioning of VPg. Either changing the serine residue linking VPg to RNA at a tyrosine or a threonine or changing the

Fueling the Future with Fungal Genomes

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor V.

2014-10-27

Genomes of fungi relevant to energy and environment are in focus of the JGI Fungal Genomic Program. One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts and pathogens) and biorefinery processes (cellulose degradation and sugar fermentation) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Science Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for users to nominate new species for sequencing. Over 400 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics will lead to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such ‘parts’ suggested by comparative genomics and functional analysis in these areas are presented here.

Genome-Wide Identification and Structural Analysis of bZIP Transcription Factor Genes in Brassica napus.

Science.gov (United States)

Zhou, Yan; Xu, Daixiang; Jia, Ledong; Huang, Xiaohu; Ma, Guoqiang; Wang, Shuxian; Zhu, Meichen; Zhang, Aoxiang; Guan, Mingwei; Lu, Kun; Xu, Xinfu; Wang, Rui; Li, Jiana; Qu, Cunmin

2017-10-24

The basic region/leucine zipper motif (bZIP) transcription factor family is one of the largest families of transcriptional regulators in plants. bZIP genes have been systematically characterized in some plants, but not in rapeseed ( Brassica napus ). In this study, we identified 247 BnbZIP genes in the rapeseed genome, which we classified into 10 subfamilies based on phylogenetic analysis of their deduced protein sequences. The BnbZIP genes were grouped into functional clades with Arabidopsis genes with similar putative functions, indicating functional conservation. Genome mapping analysis revealed that the BnbZIPs are distributed unevenly across all 19 chromosomes, and that some of these genes arose through whole-genome duplication and dispersed duplication events. All expression profiles of 247 bZIP genes were extracted from RNA-sequencing data obtained from 17 different B . napus ZS11 tissues with 42 various developmental stages. These genes exhibited different expression patterns in various tissues, revealing that these genes are differentially regulated. Our results provide a valuable foundation for functional dissection of the different BnbZIP homologs in B . napus and its parental lines and for molecular breeding studies of bZIP genes in B . napus .

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

Proteome scale identification, classification and structural analysis of iron-binding proteins in bread wheat.

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Verma, Shailender Kumar; Sharma, Ankita; Sandhu, Padmani; Choudhary, Neha; Sharma, Shailaja; Acharya, Vishal; Akhter, Yusuf

2017-05-01

Bread wheat is one of the major staple foods of worldwide population and iron plays a significant role in growth and development of the plant. In this report, we are presenting the genome wide identification of iron-binding proteins in bread wheat. The wheat genome derived putative proteome was screened for identification of iron-binding sequence motifs. Out of 602 putative iron-binding proteins, 130 were able to produce reliable structural models by homology techniques and further analyzed for the presence of iron-binding structural motifs. The computationally identified proteins appear to bind to ferrous and ferric ions and showed diverse coordination geometries. Glu, His, Asp and Cys amino acid residues were found to be mostly involved in iron binding. We have classified these proteins on the basis of their localization in the different cellular compartments. The identified proteins were further classified into their protein folds, families and functional classes ranging from structure maintenance of cellular components, regulation of gene expression, post translational modification, membrane proteins, enzymes, signaling and storage proteins. This comprehensive report regarding structural iron binding proteome provides useful insights into the diversity of iron binding proteins of wheat plants and further utilized to study their roles in plant growth, development and physiology. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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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.

Structural analysis of a set of proteins resulting from a bacterial genomics project.

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Badger, J; Sauder, J M; Adams, J M; Antonysamy, S; Bain, K; Bergseid, M G; Buchanan, S G; Buchanan, M D; Batiyenko, Y; Christopher, J A; Emtage, S; Eroshkina, A; Feil, I; Furlong, E B; Gajiwala, K S; Gao, X; He, D; Hendle, J; Huber, A; Hoda, K; Kearins, P; Kissinger, C; Laubert, B; Lewis, H A; Lin, J; Loomis, K; Lorimer, D; Louie, G; Maletic, M; Marsh, C D; Miller, I; Molinari, J; Muller-Dieckmann, H J; Newman, J M; Noland, B W; Pagarigan, B; Park, F; Peat, T S; Post, K W; Radojicic, S; Ramos, A; Romero, R; Rutter, M E; Sanderson, W E; Schwinn, K D; Tresser, J; Winhoven, J; Wright, T A; Wu, L; Xu, J; Harris, T J R

2005-09-01

The targets of the Structural GenomiX (SGX) bacterial genomics project were proteins conserved in multiple prokaryotic organisms with no obvious sequence homolog in the Protein Data Bank of known structures. The outcome of this work was 80 structures, covering 60 unique sequences and 49 different genes. Experimental phase determination from proteins incorporating Se-Met was carried out for 45 structures with most of the remainder solved by molecular replacement using members of the experimentally phased set as search models. An automated tool was developed to deposit these structures in the Protein Data Bank, along with the associated X-ray diffraction data (including refined experimental phases) and experimentally confirmed sequences. BLAST comparisons of the SGX structures with structures that had appeared in the Protein Data Bank over the intervening 3.5 years since the SGX target list had been compiled identified homologs for 49 of the 60 unique sequences represented by the SGX structures. This result indicates that, for bacterial structures that are relatively easy to express, purify, and crystallize, the structural coverage of gene space is proceeding rapidly. More distant sequence-structure relationships between the SGX and PDB structures were investigated using PDB-BLAST and Combinatorial Extension (CE). Only one structure, SufD, has a truly unique topology compared to all folds in the PDB. Copyright 2005 Wiley-Liss, Inc.

Evidence-based gene models for structural and functional annotations of the oil palm genome.

Science.gov (United States)

Chan, Kuang-Lim; Tatarinova, Tatiana V; Rosli, Rozana; Amiruddin, Nadzirah; Azizi, Norazah; Halim, Mohd Amin Ab; Sanusi, Nik Shazana Nik Mohd; Jayanthi, Nagappan; Ponomarenko, Petr; Triska, Martin; Solovyev, Victor; Firdaus-Raih, Mohd; Sambanthamurthi, Ravigadevi; Murphy, Denis; Low, Eng-Ti Leslie

2017-09-08

Oil palm is an important source of edible oil. The importance of the crop, as well as its long breeding cycle (10-12 years) has led to the sequencing of its genome in 2013 to pave the way for genomics-guided breeding. Nevertheless, the first set of gene predictions, although useful, had many fragmented genes. Classification and characterization of genes associated with traits of interest, such as those for fatty acid biosynthesis and disease resistance, were also limited. Lipid-, especially fatty acid (FA)-related genes are of particular interest for the oil palm as they specify oil yields and quality. This paper presents the characterization of the oil palm genome using different gene prediction methods and comparative genomics analysis, identification of FA biosynthesis and disease resistance genes, and the development of an annotation database and bioinformatics tools. Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC 3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC 3 -rich genes (GC 3  ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures. We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC 3 -rich and intronless), as well as those associated with important functions, such as FA

Analysis of small scale turbulent structures and the effect of spatial scales on gas transfer

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Schnieders, Jana; Garbe, Christoph

2014-05-01

The exchange of gases through the air-sea interface strongly depends on environmental conditions such as wind stress and waves which in turn generate near surface turbulence. Near surface turbulence is a main driver of surface divergence which has been shown to cause highly variable transfer rates on relatively small spatial scales. Due to the cool skin of the ocean, heat can be used as a tracer to detect areas of surface convergence and thus gather information about size and intensity of a turbulent process. We use infrared imagery to visualize near surface aqueous turbulence and determine the impact of turbulent scales on exchange rates. Through the high temporal and spatial resolution of these types of measurements spatial scales as well as surface dynamics can be captured. The surface heat pattern is formed by distinct structures on two scales - small-scale short lived structures termed fish scales and larger scale cold streaks that are consistent with the footprints of Langmuir Circulations. There are two key characteristics of the observed surface heat patterns: 1. The surface heat patterns show characteristic features of scales. 2. The structure of these patterns change with increasing wind stress and surface conditions. In [2] turbulent cell sizes have been shown to systematically decrease with increasing wind speed until a saturation at u* = 0.7 cm/s is reached. Results suggest a saturation in the tangential stress. Similar behaviour has been observed by [1] for gas transfer measurements at higher wind speeds. In this contribution a new model to estimate the heat flux is applied which is based on the measured turbulent cell size und surface velocities. This approach allows the direct comparison of the net effect on heat flux of eddies of different sizes and a comparison to gas transfer measurements. Linking transport models with thermographic measurements, transfer velocities can be computed. In this contribution, we will quantify the effect of small scale

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

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

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.

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.

Leishmania naiffi and Leishmania guyanensis reference genomes highlight genome structure and gene evolution in the Viannia subgenus.

Science.gov (United States)

Coughlan, Simone; Taylor, Ali Shirley; Feane, Eoghan; Sanders, Mandy; Schonian, Gabriele; Cotton, James A; Downing, Tim

2018-04-01

The unicellular protozoan parasite Leishmania causes the neglected tropical disease leishmaniasis, affecting 12 million people in 98 countries. In South America, where the Viannia subgenus predominates, so far only L. ( Viannia ) braziliensis and L. ( V. ) panamensis have been sequenced, assembled and annotated as reference genomes. Addressing this deficit in molecular information can inform species typing, epidemiological monitoring and clinical treatment. Here, L. ( V. ) naiffi and L. ( V. ) guyanensis genomic DNA was sequenced to assemble these two genomes as draft references from short sequence reads. The methods used were tested using short sequence reads for L. braziliensis M2904 against its published reference as a comparison. This assembly and annotation pipeline identified 70 additional genes not annotated on the original M2904 reference. Phylogenetic and evolutionary comparisons of L. guyanensis and L. naiffi with 10 other Viannia genomes revealed four traits common to all Viannia : aneuploidy, 22 orthologous groups of genes absent in other Leishmania subgenera, elevated TATE transposon copies and a high NADH-dependent fumarate reductase gene copy number. Within the Viannia , there were limited structural changes in genome architecture specific to individual species: a 45 Kb amplification on chromosome 34 was present in all bar L. lainsoni , L. naiffi had a higher copy number of the virulence factor leishmanolysin, and laboratory isolate L. shawi M8408 had a possible minichromosome derived from the 3' end of chromosome 34 . This combination of genome assembly, phylogenetics and comparative analysis across an extended panel of diverse Viannia has uncovered new insights into the origin and evolution of this subgenus and can help improve diagnostics for leishmaniasis surveillance.

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.

A genome wide survey of SNP variation reveals the genetic structure of sheep breeds.

Directory of Open Access Journals (Sweden)

James W Kijas

Full Text Available The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability.

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

Processor farming method for multi-scale analysis of masonry structures

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Krejčí, Tomáš; Koudelka, Tomáš

2017-07-01

This paper describes a processor farming method for a coupled heat and moisture transport in masonry using a two-level approach. The motivation for the two-level description comes from difficulties connected with masonry structures, where the size of stone blocks is much larger than the size of mortar layers and very fine finite element mesh has to be used. The two-level approach is suitable for parallel computing because nearly all computations can be performed independently with little synchronization. This approach is called processor farming. The master processor is dealing with the macro-scale level - the structure and the slave processors are dealing with a homogenization procedure on the meso-scale level which is represented by an appropriate representative volume element.

Software for computing and annotating genomic ranges.

Science.gov (United States)

Lawrence, Michael; Huber, Wolfgang; Pagès, Hervé; Aboyoun, Patrick; Carlson, Marc; Gentleman, Robert; Morgan, Martin T; Carey, Vincent J

2013-01-01

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

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

Genome-wide identification and structure-function studies of proteases and protease inhibitors in Cicer arietinum (chickpea).

Science.gov (United States)

Sharma, Ranu; Suresh, C G

2015-01-01

Proteases are a family of enzymes present in almost all living organisms. In plants they are involved in many biological processes requiring stress response in situations such as water deficiency, pathogen attack, maintaining protein content of the cell, programmed cell death, senescence, reproduction and many more. Similarly, protease inhibitors (PIs) are involved in various important functions like suppression of invasion by pathogenic nematodes, inhibition of spores-germination and mycelium growth of Alternaria alternata and response to wounding and fungal attack. As much as we know, no genome-wide study of proteases together with proteinaceous PIs is reported in any of the sequenced genomes till now. Phylogenetic studies and domain analysis of proteases were carried out to understand the molecular evolution as well as gene and protein features. Structural analysis was carried out to explore the binding mode and affinity of PIs for cognate proteases and prolyl oligopeptidase protease with inhibitor ligand. In the study reported here, a significant number of proteases and PIs were identified in chickpea genome. The gene expression profiles of proteases and PIs in five different plant tissues revealed a differential expression pattern in more than one plant tissue. Molecular dynamics studies revealed the formation of stable complex owing to increased number of protein-ligand and inter and intramolecular protein-protein hydrogen bonds. The genome-wide identification, characterization, evolutionary understanding, gene expression, and structural analysis of proteases and PIs provide a framework for future analysis when defining their roles in stress response and developing a more stress tolerant variety of chickpea. Copyright © 2014 Elsevier Ltd. All rights reserved.

A four-scale homogenization analysis of creep of a nuclear containment structure

Energy Technology Data Exchange (ETDEWEB)

Tran, A.B. [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Échelle, MSME UMR 8208 CNRS, 5 bd Descartes, F-77454 Marne-la-Vallée (France); EDF R and D – Département MMC Site des Renardières – Avenue des Renardières - Ecuelles, 77818 Moret sur Loing Cedex (France); Department of Applied Informatics in Construction, National University of Civil Engineering, 55 Giai Phong Road, Hai Ba Trung District, Hanoi (Viet Nam); Yvonnet, J., E-mail: julien.yvonnet@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Échelle, MSME UMR 8208 CNRS, 5 bd Descartes, F-77454 Marne-la-Vallée (France); He, Q.-C. [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Échelle, MSME UMR 8208 CNRS, 5 bd Descartes, F-77454 Marne-la-Vallée (France); Toulemonde, C.; Sanahuja, J. [EDF R and D – Département MMC Site des Renardières – Avenue des Renardières - Ecuelles, 77818 Moret sur Loing Cedex (France)

2013-12-15

A four-scale approach is proposed to predict the creep behavior of a concrete structure. The behavior of concrete is modeled through a numerical multiscale methodology, by successively homogenizing the viscoelastic behavior at different scales, starting from the cement paste. The homogenization is carried out by numerically constructing an effective relaxation tensor at each scale. In this framework, the impact of modifying the microstructural parameters can be directly observed on the structure response, like the interaction of the creep of concrete with the prestressing tendons network, and the effects of an internal pressure which might occur during a nuclear accident.

A four-scale homogenization analysis of creep of a nuclear containment structure

International Nuclear Information System (INIS)

Tran, A.B.; Yvonnet, J.; He, Q.-C.; Toulemonde, C.; Sanahuja, J.

2013-01-01

A four-scale approach is proposed to predict the creep behavior of a concrete structure. The behavior of concrete is modeled through a numerical multiscale methodology, by successively homogenizing the viscoelastic behavior at different scales, starting from the cement paste. The homogenization is carried out by numerically constructing an effective relaxation tensor at each scale. In this framework, the impact of modifying the microstructural parameters can be directly observed on the structure response, like the interaction of the creep of concrete with the prestressing tendons network, and the effects of an internal pressure which might occur during a nuclear accident

Comparative genomics of the relationship between gene structure and expression

NARCIS (Netherlands)

Ren, X.

2006-01-01

The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene

The topology of large-scale structure. III. Analysis of observations

International Nuclear Information System (INIS)

Gott, J.R. III; Weinberg, D.H.; Miller, J.; Thuan, T.X.; Schneider, S.E.

1989-01-01