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

Science.gov (United States)

Song, Yun S.

2012-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

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.

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

Analysing human genomes at different scales

DEFF Research Database (Denmark)

Liu, Siyang

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

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

KAUST Repository

Thind, Anupriya Kaur

2018-02-08

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

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...

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

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

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Jensen Paul A

2011-09-01

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

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

Directory of Open Access Journals (Sweden)

Shade Larry L

2006-06-01

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

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

Science.gov (United States)

Mackey, Aaron J; Pearson, William R

2004-10-01

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

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

Science.gov (United States)

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

2007-04-26

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

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

Directory of Open Access Journals (Sweden)

Gould John

2007-04-01

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

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

Directory of Open Access Journals (Sweden)

Liu Lili

2013-06-01

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

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

Science.gov (United States)

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

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

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...

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.

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

Science.gov (United States)

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

2013-05-08

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

GWAMA: software for genome-wide association meta-analysis

Directory of Open Access Journals (Sweden)

Mägi Reedik

2010-05-01

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

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

Science.gov (United States)

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

2012-01-01

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

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.

Multi-scale structural community organisation of the human genome.

Science.gov (United States)

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

2017-04-11

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

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....

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

Science.gov (United States)

Chechetkin, V R; Lobzin, V V

2017-08-07

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

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

Science.gov (United States)

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

2017-01-01

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

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.

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

Science.gov (United States)

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

2013-09-01

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

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.

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

Science.gov (United States)

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

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

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-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...

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.

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.

FGWAS: Functional genome wide association analysis.

Science.gov (United States)

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

2017-10-01

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

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

Metabolite coupling in genome-scale metabolic networks

Directory of Open Access Journals (Sweden)

Palsson Bernhard Ø

2006-03-01

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

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.

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.

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.

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.

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

Science.gov (United States)

Yang, Yilong; Davis, Thomas M

2017-12-01

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

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-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

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

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.

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.

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

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.

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.

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

Directory of Open Access Journals (Sweden)

Sheina B. Sim

2017-06-01

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

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

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

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.

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.

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

Science.gov (United States)

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

2004-03-01

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

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

Science.gov (United States)

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

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

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

Science.gov (United States)

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

2015-01-20

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

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

Science.gov (United States)

Klier, Christine

2012-03-06

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

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...

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.

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

Science.gov (United States)

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

2013-11-01

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

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

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.

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.

Directory of Open Access Journals (Sweden)

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.

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

Krithika Bhuvaneshwar

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Settles Matthew L

2009-05-01

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

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.

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

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

Science.gov (United States)

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

2016-08-05

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

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.

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

Directory of Open Access Journals (Sweden)

David L. Oldeschulte

2017-09-01

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

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.

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.

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

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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

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.

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

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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.

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.

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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.

Genome-wide analysis of Tol2 transposon reintegration in zebrafish.

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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.

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

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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

Genome-wide comparative analysis of four Indian Drosophila species.

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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

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

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.

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

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Joelle Amselem

2011-08-01

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

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.

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.

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.

Estimating phylogenetic trees from genome-scale data.

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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.

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.

Science.gov (United States)

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

2016-01-01

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

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.

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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

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.

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

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

Science.gov (United States)

Ghosh, Debashis; Chinnaiyan, Arul M

2009-01-01

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

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.

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.

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

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

Fungal Genomics for Energy and Environment

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor V.

2013-03-11

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Sequencing 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 200 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 leads 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 Sequencing and Analysis Conference IV

Energy Technology Data Exchange (ETDEWEB)

1993-12-31

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

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

Directory of Open Access Journals (Sweden)

Nicola Mulder

2017-11-01

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

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

Science.gov (United States)

Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

OpenAIRE

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

2017-01-01

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

Construction of a plant-transformation-competent BIBAC library and genome sequence analysis of polyploid Upland cotton (Gossypium hirsutum L.).

Science.gov (United States)

Lee, Mi-Kyung; Zhang, Yang; Zhang, Meiping; Goebel, Mark; Kim, Hee Jin; Triplett, Barbara A; Stelly, David M; Zhang, Hong-Bin

2013-03-28

. raimondii contains a D genome (D5). The library represents the first BIBAC library in cotton and related species, thus providing tools useful for integrative physical mapping, large-scale genome sequencing and large-scale functional analysis of the Upland cotton genome. Comparative sequence analysis provides insights into the Upland cotton genome, and a possible mechanism underlying the divergence and evolution of polyploid Upland cotton from its diploid putative progenitor species, G. raimondii.

Large-scale parallel genome assembler over cloud computing environment.

Science.gov (United States)

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

2017-06-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

A novel statistic for genome-wide interaction analysis.

Directory of Open Access Journals (Sweden)

Xuesen Wu

2010-09-01

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

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

Science.gov (United States)

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

2014-01-01

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

Large-scale gene function analysis with the PANTHER classification system.

Science.gov (United States)

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Genome-scale analysis of aberrant DNA methylation in colorectal cancer

Science.gov (United States)

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

2012-01-01

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

A high-quality carrot genome assembly provides new insights into carotenoid accumulation and asterid genome evolution

Science.gov (United States)

We report a chromosome-scale assembly and analysis of the Daucus carota genome, an important source of provitamin A in the human diet and the first sequenced genome among members of the Euasterid II clade. We characterized two new polyploidization events, both occurring after the divergence of carro...

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

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

2006-05-19

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

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

Directory of Open Access Journals (Sweden)

Stephen B Montgomery

2011-07-01

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

Differential DNA Methylation Analysis without a Reference Genome

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Johanna Klughammer

2015-12-01

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

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

Science.gov (United States)

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

2017-04-01

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

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

Science.gov (United States)

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

2013-07-16

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

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2016-06-01

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

CoryneCenter – An online resource for the integrated analysis of corynebacterial genome and transcriptome data

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Hüser Andrea T

2007-11-01

Full Text Available Abstract Background The introduction of high-throughput genome sequencing and post-genome analysis technologies, e.g. DNA microarray approaches, has created the potential to unravel and scrutinize complex gene-regulatory networks on a large scale. The discovery of transcriptional regulatory interactions has become a major topic in modern functional genomics. Results To facilitate the analysis of gene-regulatory networks, we have developed CoryneCenter, a web-based resource for the systematic integration and analysis of genome, transcriptome, and gene regulatory information for prokaryotes, especially corynebacteria. For this purpose, we extended and combined the following systems into a common platform: (1 GenDB, an open source genome annotation system, (2 EMMA, a MAGE compliant application for high-throughput transcriptome data storage and analysis, and (3 CoryneRegNet, an ontology-based data warehouse designed to facilitate the reconstruction and analysis of gene regulatory interactions. We demonstrate the potential of CoryneCenter by means of an application example. Using microarray hybridization data, we compare the gene expression of Corynebacterium glutamicum under acetate and glucose feeding conditions: Known regulatory networks are confirmed, but moreover CoryneCenter points out additional regulatory interactions. Conclusion CoryneCenter provides more than the sum of its parts. Its novel analysis and visualization features significantly simplify the process of obtaining new biological insights into complex regulatory systems. Although the platform currently focusses on corynebacteria, the integrated tools are by no means restricted to these species, and the presented approach offers a general strategy for the analysis and verification of gene regulatory networks. CoryneCenter provides freely accessible projects with the underlying genome annotation, gene expression, and gene regulation data. The system is publicly available at http://www.CoryneCenter.de.

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.

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

Energy Technology Data Exchange (ETDEWEB)

Navid, A; Almaas, E

2009-01-13

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

IMG: the integrated microbial genomes database and comparative analysis system

Science.gov (United States)

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

2012-01-01

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

From human monocytes to genome-wide binding sites--a protocol for small amounts of blood: monocyte isolation/ChIP-protocol/library amplification/genome wide computational data analysis.

Directory of Open Access Journals (Sweden)

Sebastian Weiterer

Full Text Available Chromatin immunoprecipitation in combination with a genome-wide analysis via high-throughput sequencing is the state of the art method to gain genome-wide representation of histone modification or transcription factor binding profiles. However, chromatin immunoprecipitation analysis in the context of human experimental samples is limited, especially in the case of blood cells. The typically extremely low yields of precipitated DNA are usually not compatible with library amplification for next generation sequencing. We developed a highly reproducible protocol to present a guideline from the first step of isolating monocytes from a blood sample to analyse the distribution of histone modifications in a genome-wide manner.The protocol describes the whole work flow from isolating monocytes from human blood samples followed by a high-sensitivity and small-scale chromatin immunoprecipitation assay with guidance for generating libraries compatible with next generation sequencing from small amounts of immunoprecipitated DNA.

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

Science.gov (United States)

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

2016-09-01

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

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

LENUS (Irish Health Repository)

Sklar, Pamela

2011-10-01

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

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...

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

Science.gov (United States)

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

2016-08-20

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

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

Science.gov (United States)

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction

EUPAN enables pan-genome studies of a large number of eukaryotic genomes.

Science.gov (United States)

Hu, Zhiqiang; Sun, Chen; Lu, Kuang-Chen; Chu, Xixia; Zhao, Yue; Lu, Jinyuan; Shi, Jianxin; Wei, Chaochun

2017-08-01

Pan-genome analyses are routinely carried out for bacteria to interpret the within-species gene presence/absence variations (PAVs). However, pan-genome analyses are rare for eukaryotes due to the large sizes and higher complexities of their genomes. Here we proposed EUPAN, a eukaryotic pan-genome analysis toolkit, enabling automatic large-scale eukaryotic pan-genome analyses and detection of gene PAVs at a relatively low sequencing depth. In the previous studies, we demonstrated the effectiveness and high accuracy of EUPAN in the pan-genome analysis of 453 rice genomes, in which we also revealed widespread gene PAVs among individual rice genomes. Moreover, EUPAN can be directly applied to the current re-sequencing projects primarily focusing on single nucleotide polymorphisms. EUPAN is implemented in Perl, R and C ++. It is supported under Linux and preferred for a computer cluster with LSF and SLURM job scheduling system. EUPAN together with its standard operating procedure (SOP) is freely available for non-commercial use (CC BY-NC 4.0) at http://cgm.sjtu.edu.cn/eupan/index.html . ccwei@sjtu.edu.cn or jianxin.shi@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Comparative genome analysis of Basidiomycete fungi

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

2013-08-07

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

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

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

Science.gov (United States)

Barnes, Kayla G; Weedall, Gareth D; Ndula, Miranda; Irving, Helen; Mzihalowa, Themba; Hemingway, Janet; Wondji, Charles S

2017-02-01

Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

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

Directory of Open Access Journals (Sweden)

Kayla G Barnes

2017-02-01

Full Text Available Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

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

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

2008-06-18

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

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

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Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

Genomic Diversity and Evolution of the Lyssaviruses

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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.

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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.

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

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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

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

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

2017-01-01

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

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

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Matthias Christen

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

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

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

2011-01-01

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

Comparative analysis of the mitochondrial genomes in gastropods

International Nuclear Information System (INIS)

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

2012-01-01

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

Mycobacterial species as case-study of comparative genome analysis.

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

2011-02-08

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

Phylogenomic Analysis and Dynamic Evolution of Chloroplast Genomes in Salicaceae

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Yuan Huang

2017-06-01

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

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...

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

BFAST: an alignment tool for large scale genome resequencing.

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Nils Homer

2009-11-01

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

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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

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Byrappa Venkatesh

2007-04-01

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

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

NARCIS (Netherlands)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Tyler W. H. Backman

2018-01-01

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

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

Science.gov (United States)

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

2013-05-01

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

Genome-wide association study to identify common variants associated with brachial circumference: a meta-analysis of 14 cohorts.

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Vesna Boraska

Full Text Available Brachial circumference (BC, also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05 in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Katsunori Yoshikawa

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

Millstone: software for multiplex microbial genome analysis and engineering.

Science.gov (United States)

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

2017-05-25

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

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

Directory of Open Access Journals (Sweden)

Héloïse Bastide

2013-06-01

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

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

Science.gov (United States)

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

2013-06-01

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

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

NARCIS (Netherlands)

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

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

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

DEFF Research Database (Denmark)

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara

2015-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Jolly Emmitt R

2005-11-01

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

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-wide DNA polymorphism analyses using VariScan

Directory of Open Access Journals (Sweden)

Vilella Albert J

2006-09-01

Full Text Available Abstract Background DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. Results We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i exhaustive population-genetic analyses including those based on the coalescent theory; ii analysis adapted to the shallow data generated by the high-throughput genome projects; iii use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v visualization of the results integrated with current genome annotations in commonly available genome browsers. Conclusion VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.

Whole genome sequence analysis of Mycobacterium suricattae

KAUST Repository

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

2015-01-01

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

Whole genome sequence analysis of Mycobacterium suricattae

KAUST Repository

Dippenaar, Anzaan

2015-10-21

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

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.

SQC: secure quality control for meta-analysis of genome-wide association studies.

Science.gov (United States)

Huang, Zhicong; Lin, Huang; Fellay, Jacques; Kutalik, Zoltán; Hubaux, Jean-Pierre

2017-08-01

Due to the limited power of small-scale genome-wide association studies (GWAS), researchers tend to collaborate and establish a larger consortium in order to perform large-scale GWAS. Genome-wide association meta-analysis (GWAMA) is a statistical tool that aims to synthesize results from multiple independent studies to increase the statistical power and reduce false-positive findings of GWAS. However, it has been demonstrated that the aggregate data of individual studies are subject to inference attacks, hence privacy concerns arise when researchers share study data in GWAMA. In this article, we propose a secure quality control (SQC) protocol, which enables checking the quality of data in a privacy-preserving way without revealing sensitive information to a potential adversary. SQC employs state-of-the-art cryptographic and statistical techniques for privacy protection. We implement the solution in a meta-analysis pipeline with real data to demonstrate the efficiency and scalability on commodity machines. The distributed execution of SQC on a cluster of 128 cores for one million genetic variants takes less than one hour, which is a modest cost considering the 10-month time span usually observed for the completion of the QC procedure that includes timing of logistics. SQC is implemented in Java and is publicly available at https://github.com/acs6610987/secureqc. jean-pierre.hubaux@epfl.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

Directory of Open Access Journals (Sweden)

Wang Jintu

2011-04-01

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

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

Science.gov (United States)

2011-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

A Distance Measure for Genome Phylogenetic Analysis

Science.gov (United States)

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

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

Microbial Genome Analysis and Comparisons: Web-based Protocols and Resources

Science.gov (United States)

Fully annotated genome sequences of many microorganisms are publicly available as a resource. However, in-depth analysis of these genomes using specialized tools is required to derive meaningful information. We describe here the utility of three powerful publicly available genome databases and ana...

Genome-wide analysis of wild-type Epstein-Barr virus genomes derived from healthy individuals of the 1,000 Genomes Project.

Science.gov (United States)

Santpere, Gabriel; Darre, Fleur; Blanco, Soledad; Alcami, Antonio; Villoslada, Pablo; Mar Albà, M; Navarro, Arcadi

2014-04-01

Most people in the world (∼90%) are infected by the Epstein-Barr virus (EBV), which establishes itself permanently in B cells. Infection by EBV is related to a number of diseases including infectious mononucleosis, multiple sclerosis, and different types of cancer. So far, only seven complete EBV strains have been described, all of them coming from donors presenting EBV-related diseases. To perform a detailed comparative genomic analysis of EBV including, for the first time, EBV strains derived from healthy individuals, we reconstructed EBV sequences infecting lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project. As strain B95-8 was used to transform B cells to obtain LCLs, it is always present, but a specific deletion in its genome sets it apart from natural EBV strains. After studying hundreds of individuals, we determined the presence of natural EBV in at least 10 of them and obtained a set of variants specific to wild-type EBV. By mapping the natural EBV reads into the EBV reference genome (NC007605), we constructed nearly complete wild-type viral genomes from three individuals. Adding them to the five disease-derived EBV genomic sequences available in the literature, we performed an in-depth comparative genomic analysis. We found that latency genes harbor more nucleotide diversity than lytic genes and that six out of nine latency-related genes, as well as other genes involved in viral attachment and entry into host cells, packaging, and the capsid, present the molecular signature of accelerated protein evolution rates, suggesting rapid host-parasite coevolution.

Genome analysis and DNA marker-based characterisation of pathogenic trypanosomes

NARCIS (Netherlands)

Agbo, Edwin Chukwura

2003-01-01

The advances in genomics technologies and genome analysis methods that offer new leads for accelerating discovery of putative targets for developing overall control tools are reviewed in Chapter 1. In Chapter 2, a PCR typing method based on restriction fragment length polymorphism analysis of the

MIPS: analysis and annotation of proteins from whole genomes.

Science.gov (United States)

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

2004-01-01

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

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).

PCR-SSCP analysis and its application to human genome study

International Nuclear Information System (INIS)

Hayashi, Kenshi

1994-01-01

A large amount of DNA sequence data are now available owing to the development of the human genome project. These data are deposited in public databases, e.g. DDBJ, GebBank and EMBL, and freely accessible to scientific community. One of the major advantages of having these databases is that we can now detect sequence differences between individuals in a large scale. Using the sequence informations, we can design primer sequences, amplify various target regions of the sample DNA's by PCR and detect abnormal sequence changes from reference, or normal sequences. Detecting sequence changes, or mutations, are essential part of searching genes responsible for hereditary diseases and also DNA diagnosis of hereditary diseases or cancer. We can also measure mutation frequency of the human genome by knowing its variability. Our group has developed and been improving a method, PCR-SSCP analysis, as an extremely rapid and easy technique for detection of sequence differences between sample DNA's. Knowing the sensitivity (percentage detection of mutations) of this technique is important in evaluating usefulness of it for the purposes stated above. Considerable number of experiences on PCR-SSCP analysis of fragments shorter than 300 b.p. are accumulating. We summarize here the sensitivity of PCR-SSCP analysis for various sequence context of this size range examined in various electrophoretic conditions conducted in many laboratories. Data on mutation detection by this technique for longer fragments are limited. We also present oue effort for defining electrophoretic conditions of PCR-SSCP analysis when examining longer (350 to 600 b.p.) fragments. (author)

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

Directory of Open Access Journals (Sweden)

RICARDO CRUZ-COKE

2001-03-01

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

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.

Genome-scale modeling of the protein secretory machinery in yeast

DEFF Research Database (Denmark)

Feizi, Amir; Österlund, Tobias; Petranovic, Dina

2013-01-01

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

Comparative genomic analysis by microbial COGs self-attraction rate.

Science.gov (United States)

Santoni, Daniele; Romano-Spica, Vincenzo

2009-06-21

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

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

NARCIS (Netherlands)

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

2009-01-01

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

Approaches for Comparative Genomics in Aspergillus and Penicillium

DEFF Research Database (Denmark)

Rasmussen, Jane Lind Nybo; Theobald, Sebastian; Brandl, Julian

2016-01-01

and applicable for many types of studies. In this chapter, we provide an overview of the state-of-the-art of comparative genomics in these fungi, along with recommended methods. The chapter describes databases for fungal comparative genomics. Based on experience, we suggest strategies for multiple types...... of comparative genomics, ranging from analysis of single genes, over gene clusters and CaZymes to genome-scale comparative genomics. Furthermore, we have examined published comparative genomics papers to summarize the preferred bioinformatic methods and parameters for a given type of analysis, highly useful...... comparative genomics to the development in bacterial genomics, where the comparison of hundreds of genomes has been performed for a while....

Comparative Genome Analysis and Genome Evolution

NARCIS (Netherlands)

Snel, Berend

2002-01-01

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

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

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

DEFF Research Database (Denmark)

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

2018-01-01

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

A review of genome-wide approaches to study the genetic basis for spermatogenic defects.

Science.gov (United States)

Aston, Kenneth I; Conrad, Donald F

2013-01-01

Rapidly advancing tools for genetic analysis on a genome-wide scale have been instrumental in identifying the genetic bases for many complex diseases. About half of male infertility cases are of unknown etiology in spite of tremendous efforts to characterize the genetic basis for the disorder. Advancing our understanding of the genetic basis for male infertility will require the application of established and emerging genomic tools. This chapter introduces many of the tools available for genetic studies on a genome-wide scale along with principles of study design and data analysis.

Insights from Human/Mouse genome comparisons

Energy Technology Data Exchange (ETDEWEB)

Pennacchio, Len A.

2003-03-30

Large-scale public genomic sequencing efforts have provided a wealth of vertebrate sequence data poised to provide insights into mammalian biology. These include deep genomic sequence coverage of human, mouse, rat, zebrafish, and two pufferfish (Fugu rubripes and Tetraodon nigroviridis) (Aparicio et al. 2002; Lander et al. 2001; Venter et al. 2001; Waterston et al. 2002). In addition, a high-priority has been placed on determining the genomic sequence of chimpanzee, dog, cow, frog, and chicken (Boguski 2002). While only recently available, whole genome sequence data have provided the unique opportunity to globally compare complete genome contents. Furthermore, the shared evolutionary ancestry of vertebrate species has allowed the development of comparative genomic approaches to identify ancient conserved sequences with functionality. Accordingly, this review focuses on the initial comparison of available mammalian genomes and describes various insights derived from such analysis.

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

Directory of Open Access Journals (Sweden)

Laura Navone

2018-06-01

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

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

Directory of Open Access Journals (Sweden)

Nicholas R Thomson

2006-12-01

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

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

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

2013-01-01

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

Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

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Rzhetsky, A; Gomez, S M

2001-10-01

Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

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Moreau Yves

2005-05-01

Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

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

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Cook, Daniel J; Nielsen, Jens

2017-11-01

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

The Sequenced Angiosperm Genomes and Genome Databases.

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Chen, Fei; Dong, Wei; Zhang, Jiawei; Guo, Xinyue; Chen, Junhao; Wang, Zhengjia; Lin, Zhenguo; Tang, Haibao; Zhang, Liangsheng

2018-01-01

Angiosperms, the flowering plants, provide the essential resources for human life, such as food, energy, oxygen, and materials. They also promoted the evolution of human, animals, and the planet earth. Despite the numerous advances in genome reports or sequencing technologies, no review covers all the released angiosperm genomes and the genome databases for data sharing. Based on the rapid advances and innovations in the database reconstruction in the last few years, here we provide a comprehensive review for three major types of angiosperm genome databases, including databases for a single species, for a specific angiosperm clade, and for multiple angiosperm species. The scope, tools, and data of each type of databases and their features are concisely discussed. The genome databases for a single species or a clade of species are especially popular for specific group of researchers, while a timely-updated comprehensive database is more powerful for address of major scientific mysteries at the genome scale. Considering the low coverage of flowering plants in any available database, we propose construction of a comprehensive database to facilitate large-scale comparative studies of angiosperm genomes and to promote the collaborative studies of important questions in plant biology.

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.

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

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Yali eWang

2015-06-01

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

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

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

2018-02-14

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

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

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

2017-11-22

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

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

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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.

Comparative analysis of prophages in Streptococcus mutans genomes

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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

Data on genome analysis of Bacillus velezensis LS69.

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

2017-08-01

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

Data on genome analysis of Bacillus velezensis LS69

OpenAIRE

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

2017-01-01

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

An object model for genome information at all levels of resolution

Energy Technology Data Exchange (ETDEWEB)

Honda, S.; Parrott, N.W.; Smith, R.; Lawrence, C.

1993-12-31

An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.

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

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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

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

Science.gov (United States)

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

2013-07-01

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

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

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Rachael Natrajan

2016-02-01

Full Text Available The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D in solid tumors, termed the tumor ecosystem diversity index (EDI, using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3 breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2 breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52. Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.To our knowledge, this is the first

Analysis of intra-genomic GC content homogeneity within prokaryotes

DEFF Research Database (Denmark)

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

2010-01-01

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

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

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Fang, Yilin; Yabusaki, Steven B.; Lipton, Mary S.; Long, Philip E.

2012-01-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment. PMID:23042184

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

Science.gov (United States)

Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

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

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

DEFF Research Database (Denmark)

Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

2015-01-01

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

Data on genome analysis of Bacillus velezensis LS69

Directory of Open Access Journals (Sweden)

Guoqiang Liu

2017-08-01

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

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.

Assembly of 500,000 inter-specific catfish expressed sequence tags and large scale gene-associated marker development for whole genome association studies

Energy Technology Data Exchange (ETDEWEB)

Catfish Genome Consortium; Wang, Shaolin; Peatman, Eric; Abernathy, Jason; Waldbieser, Geoff; Lindquist, Erika; Richardson, Paul; Lucas, Susan; Wang, Mei; Li, Ping; Thimmapuram, Jyothi; Liu, Lei; Vullaganti, Deepika; Kucuktas, Huseyin; Murdock, Christopher; Small, Brian C; Wilson, Melanie; Liu, Hong; Jiang, Yanliang; Lee, Yoona; Chen, Fei; Lu, Jianguo; Wang, Wenqi; Xu, Peng; Somridhivej, Benjaporn; Baoprasertkul, Puttharat; Quilang, Jonas; Sha, Zhenxia; Bao, Baolong; Wang, Yaping; Wang, Qun; Takano, Tomokazu; Nandi, Samiran; Liu, Shikai; Wong, Lilian; Kaltenboeck, Ludmilla; Quiniou, Sylvie; Bengten, Eva; Miller, Norman; Trant, John; Rokhsar, Daniel; Liu, Zhanjiang

2010-03-23

Background-Through the Community Sequencing Program, a catfish EST sequencing project was carried out through a collaboration between the catfish research community and the Department of Energy's Joint Genome Institute. Prior to this project, only a limited EST resource from catfish was available for the purpose of SNP identification. Results-A total of 438,321 quality ESTs were generated from 8 channel catfish (Ictalurus punctatus) and 4 blue catfish (Ictalurus furcatus) libraries, bringing the number of catfish ESTs to nearly 500,000. Assembly of all catfish ESTs resulted in 45,306 contigs and 66,272 singletons. Over 35percent of the unique sequences had significant similarities to known genes, allowing the identification of 14,776 unique genes in catfish. Over 300,000 putative SNPs have been identified, of which approximately 48,000 are high-quality SNPs identified from contigs with at least four sequences and the minor allele presence of at least two sequences in the contig. The EST resource should be valuable for identification of microsatellites, genome annotation, large-scale expression analysis, and comparative genome analysis. Conclusions-This project generated a large EST resource for catfish that captured the majority of the catfish transcriptome. The parallel analysis of ESTs from two closely related Ictalurid catfishes should also provide powerful means for the evaluation of ancient and recent gene duplications, and for the development of high-density microarrays in catfish. The inter- and intra-specific SNPs identified from all catfish EST dataset assembly will greatly benefit the catfish introgression breeding program and whole genome association studies.

Creation and genomic analysis of irradiation hybrids in Populus

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

2016-01-01

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

Analysis of the Complete Mitochondrial Genome Sequence of the Diploid Cotton Gossypium raimondii by Comparative Genomics Approaches

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Changwei Bi

2016-01-01

Full Text Available Cotton is one of the most important economic crops and the primary source of natural fiber and is an important protein source for animal feed. The complete nuclear and chloroplast (cp genome sequences of G. raimondii are already available but not mitochondria. Here, we assembled the complete mitochondrial (mt DNA sequence of G. raimondii into a circular genome of length of 676,078 bp and performed comparative analyses with other higher plants. The genome contains 39 protein-coding genes, 6 rRNA genes, and 25 tRNA genes. We also identified four larger repeats (63.9 kb, 10.6 kb, 9.1 kb, and 2.5 kb in this mt genome, which may be active in intramolecular recombination in the evolution of cotton. Strikingly, nearly all of the G. raimondii mt genome has been transferred to nucleus on Chr1, and the transfer event must be very recent. Phylogenetic analysis reveals that G. raimondii, as a member of Malvaceae, is much closer to another cotton (G. barbadense than other rosids, and the clade formed by two Gossypium species is sister to Brassicales. The G. raimondii mt genome may provide a crucial foundation for evolutionary analysis, molecular biology, and cytoplasmic male sterility in cotton and other higher plants.

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

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Wei Liu

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

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

KAUST Repository

Kamanu, Frederick Kinyua

2012-12-01

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

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

Component identification of electron transport chains in curdlan-producing Agrobacterium sp. ATCC 31749 and its genome-specific prediction using comparative genome and phylogenetic trees analysis.

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Zhang, Hongtao; Setubal, Joao Carlos; Zhan, Xiaobei; Zheng, Zhiyong; Yu, Lijun; Wu, Jianrong; Chen, Dingqiang

2011-06-01

Agrobacterium sp. ATCC 31749 (formerly named Alcaligenes faecalis var. myxogenes) is a non-pathogenic aerobic soil bacterium used in large scale biotechnological production of curdlan. However, little is known about its genomic information. DNA partial sequence of electron transport chains (ETCs) protein genes were obtained in order to understand the components of ETC and genomic-specificity in Agrobacterium sp. ATCC 31749. Degenerate primers were designed according to ETC conserved sequences in other reported species. DNA partial sequences of ETC genes in Agrobacterium sp. ATCC 31749 were cloned by the PCR method using degenerate primers. Based on comparative genomic analysis, nine electron transport elements were ascertained, including NADH ubiquinone oxidoreductase, succinate dehydrogenase complex II, complex III, cytochrome c, ubiquinone biosynthesis protein ubiB, cytochrome d terminal oxidase, cytochrome bo terminal oxidase, cytochrome cbb (3)-type terminal oxidase and cytochrome caa (3)-type terminal oxidase. Similarity and phylogenetic analyses of these genes revealed that among fully sequenced Agrobacterium species, Agrobacterium sp. ATCC 31749 is closest to Agrobacterium tumefaciens C58. Based on these results a comprehensive ETC model for Agrobacterium sp. ATCC 31749 is proposed.

Typing and comparative genome analysis of Brucella melitensis isolated from Lebanon.

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Abou Zaki, Natalia; Salloum, Tamara; Osman, Marwan; Rafei, Rayane; Hamze, Monzer; Tokajian, Sima

2017-10-16

Brucella melitensis is the main causative agent of the zoonotic disease brucellosis. This study aimed at typing and characterizing genetic variation in 33 Brucella isolates recovered from patients in Lebanon. Bruce-ladder multiplex PCR and PCR-RFLP of omp31, omp2a and omp2b were performed. Sixteen representative isolates were chosen for draft-genome sequencing and analyzed to determine variations in virulence, resistance, genomic islands, prophages and insertion sequences. Comparative whole-genome single nucleotide polymorphism analysis was also performed. The isolates were confirmed to be B. melitensis. Genome analysis revealed multiple virulence determinants and efflux pumps. Genome comparisons and single nucleotide polymorphisms divided the isolates based on geographical distribution but revealed high levels of similarity between the strains. Sequence divergence in B. melitensis was mainly due to lateral gene transfer of mobile elements. This is the first report of an in-depth genomic characterization of B. melitensis in Lebanon. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

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

2011-01-01

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

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

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Amit Ghosh

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

How do students react to analyzing their own genomes in a whole-genome sequencing course?: outcomes of a longitudinal cohort study.

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Sanderson, Saskia C; Linderman, Michael D; Zinberg, Randi; Bashir, Ali; Kasarskis, Andrew; Zweig, Micol; Suckiel, Sabrina; Shah, Hardik; Mahajan, Milind; Diaz, George A; Schadt, Eric E

2015-11-01

Health-care professionals need to be trained to work with whole-genome sequencing (WGS) in their practice. Our aim was to explore how students responded to a novel genome analysis course that included the option to analyze their own genomes. This was an observational cohort study. Questionnaires were administered before (T3) and after the genome analysis course (T4), as well as 6 months later (T5). In-depth interviews were conducted at T5. All students (n = 19) opted to analyze their own genomes. At T5, 12 of 15 students stated that analyzing their own genomes had been useful. Ten reported they had applied their knowledge in the workplace. Technical WGS knowledge increased (mean of 63.8% at T3, mean of 72.5% at T4; P = 0.005). In-depth interviews suggested that analyzing their own genomes may increase students' motivation to learn and their understanding of the patient experience. Most (but not all) of the students reported low levels of WGS results-related distress and low levels of regret about their decision to analyze their own genomes. Giving students the option of analyzing their own genomes may increase motivation to learn, but some students may experience personal WGS results-related distress and regret. Additional evidence is required before considering incorporating optional personal genome analysis into medical education on a large scale.

Analysis of high-throughput sequencing and annotation strategies for phage genomes.

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Matthew R Henn

Full Text Available BACKGROUND: Bacterial viruses (phages play a critical role in shaping microbial populations as they influence both host mortality and horizontal gene transfer. As such, they have a significant impact on local and global ecosystem function and human health. Despite their importance, little is known about the genomic diversity harbored in phages, as methods to capture complete phage genomes have been hampered by the lack of knowledge about the target genomes, and difficulties in generating sufficient quantities of genomic DNA for sequencing. Of the approximately 550 phage genomes currently available in the public domain, fewer than 5% are marine phage. METHODOLOGY/PRINCIPAL FINDINGS: To advance the study of phage biology through comparative genomic approaches we used marine cyanophage as a model system. We compared DNA preparation methodologies (DNA extraction directly from either phage lysates or CsCl purified phage particles, and sequencing strategies that utilize either Sanger sequencing of a linker amplification shotgun library (LASL or of a whole genome shotgun library (WGSL, or 454 pyrosequencing methods. We demonstrate that genomic DNA sample preparation directly from a phage lysate, combined with 454 pyrosequencing, is best suited for phage genome sequencing at scale, as this method is capable of capturing complete continuous genomes with high accuracy. In addition, we describe an automated annotation informatics pipeline that delivers high-quality annotation and yields few false positives and negatives in ORF calling. CONCLUSIONS/SIGNIFICANCE: These DNA preparation, sequencing and annotation strategies enable a high-throughput approach to the burgeoning field of phage genomics.

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

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

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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.

Cinteny: flexible analysis and visualization of synteny and genome rearrangements in multiple organisms

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Meller Jaroslaw

2007-03-01

Full Text Available Abstract Background Identifying syntenic regions, i.e., blocks of genes or other markers with evolutionary conserved order, and quantifying evolutionary relatedness between genomes in terms of chromosomal rearrangements is one of the central goals in comparative genomics. However, the analysis of synteny and the resulting assessment of genome rearrangements are sensitive to the choice of a number of arbitrary parameters that affect the detection of synteny blocks. In particular, the choice of a set of markers and the effect of different aggregation strategies, which enable coarse graining of synteny blocks and exclusion of micro-rearrangements, need to be assessed. Therefore, existing tools and resources that facilitate identification, visualization and analysis of synteny need to be further improved to provide a flexible platform for such analysis, especially in the context of multiple genomes. Results We present a new tool, Cinteny, for fast identification and analysis of synteny with different sets of markers and various levels of coarse graining of syntenic blocks. Using Hannenhalli-Pevzner approach and its extensions, Cinteny also enables interactive determination of evolutionary relationships between genomes in terms of the number of rearrangements (the reversal distance. In particular, Cinteny provides: i integration of synteny browsing with assessment of evolutionary distances for multiple genomes; ii flexibility to adjust the parameters and re-compute the results on-the-fly; iii ability to work with user provided data, such as orthologous genes, sequence tags or other conserved markers. In addition, Cinteny provides many annotated mammalian, invertebrate and fungal genomes that are pre-loaded and available for analysis at http://cinteny.cchmc.org. Conclusion Cinteny allows one to automatically compare multiple genomes and perform sensitivity analysis for synteny block detection and for the subsequent computation of reversal distances

Comparative Genomic Analysis of Soybean Flowering Genes

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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

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.

Quantitative high-resolution genomic analysis of single cancer cells.

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

2011-01-01

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

Genome-wide meta-analysis of common variant differences between men and women

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Boraska, Vesna; Jerončić, Ana; Colonna, Vincenza; Southam, Lorraine; Nyholt, Dale R.; William Rayner, Nigel; Perry, John R.B.; Toniolo, Daniela; Albrecht, Eva; Ang, Wei; Bandinelli, Stefania; Barbalic, Maja; Barroso, Inês; Beckmann, Jacques S.; Biffar, Reiner; Boomsma, Dorret; Campbell, Harry; Corre, Tanguy; Erdmann, Jeanette; Esko, Tõnu; Fischer, Krista; Franceschini, Nora; Frayling, Timothy M.; Girotto, Giorgia; Gonzalez, Juan R.; Harris, Tamara B.; Heath, Andrew C.; Heid, Iris M.; Hoffmann, Wolfgang; Hofman, Albert; Horikoshi, Momoko; Hua Zhao, Jing; Jackson, Anne U.; Hottenga, Jouke-Jan; Jula, Antti; Kähönen, Mika; Khaw, Kay-Tee; Kiemeney, Lambertus A.; Klopp, Norman; Kutalik, Zoltán; Lagou, Vasiliki; Launer, Lenore J.; Lehtimäki, Terho; Lemire, Mathieu; Lokki, Marja-Liisa; Loley, Christina; Luan, Jian'an; Mangino, Massimo; Mateo Leach, Irene; Medland, Sarah E.; Mihailov, Evelin; Montgomery, Grant W.; Navis, Gerjan; Newnham, John; Nieminen, Markku S.; Palotie, Aarno; Panoutsopoulou, Kalliope; Peters, Annette; Pirastu, Nicola; Polašek, Ozren; Rehnström, Karola; Ripatti, Samuli; Ritchie, Graham R.S.; Rivadeneira, Fernando; Robino, Antonietta; Samani, Nilesh J.; Shin, So-Youn; Sinisalo, Juha; Smit, Johannes H.; Soranzo, Nicole; Stolk, Lisette; Swinkels, Dorine W.; Tanaka, Toshiko; Teumer, Alexander; Tönjes, Anke; Traglia, Michela; Tuomilehto, Jaakko; Valsesia, Armand; van Gilst, Wiek H.; van Meurs, Joyce B.J.; Smith, Albert Vernon; Viikari, Jorma; Vink, Jacqueline M.; Waeber, Gerard; Warrington, Nicole M.; Widen, Elisabeth; Willemsen, Gonneke; Wright, Alan F.; Zanke, Brent W.; Zgaga, Lina; Boehnke, Michael; d'Adamo, Adamo Pio; de Geus, Eco; Demerath, Ellen W.; den Heijer, Martin; Eriksson, Johan G.; Ferrucci, Luigi; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Hengstenberg, Christian; Hudson, Thomas J.; Järvelin, Marjo-Riitta; Kogevinas, Manolis; Loos, Ruth J.F.; Martin, Nicholas G.; Metspalu, Andres; Pennell, Craig E.; Penninx, Brenda W.; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Schreiber, Stefan; Schunkert, Heribert; Spector, Tim D.; Stumvoll, Michael; Uitterlinden, André G.; Ulivi, Sheila; van der Harst, Pim; Vollenweider, Peter; Völzke, Henry; Wareham, Nicholas J.; Wichmann, H.-Erich; Wilson, James F.; Rudan, Igor; Xue, Yali; Zeggini, Eleftheria

2012-01-01

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10−8) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∼115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits. PMID:22843499

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

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

2016-10-19

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

Genomic Analysis of Complex Microbial Communities in Wounds

Science.gov (United States)

2012-01-01

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

Genome-Wide Detection and Analysis of Multifunctional Genes

Science.gov (United States)

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

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

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

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Elena Vinay-Lara

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

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

DEFF Research Database (Denmark)

Kjeldsen, Kjeld Raunkjær; Nielsen, J.

2009-01-01

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

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

Indian Academy of Sciences (India)

Navya

2017-02-22

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

Genomic analysis of WCP30 Phage of Weissella cibaria for Dairy Fermented Foods.

Science.gov (United States)

Lee, Young-Duck; Park, Jong-Hyun

2017-01-01

In this study, we report the morphogenetic analysis and genome sequence of a new WCP30 phage of Weissella cibaria , isolated from a fermented food. Based on its morphology, as observed by transmission electron microscopy, WCP30 phage belongs to the family Siphoviridae . Genomic analysis of WCP30 phage showed that it had a 33,697-bp double-stranded DNA genome with 41.2% G+C content. Bioinformatics analysis of the genome revealed 35 open reading frames. A BLASTN search showed that WCP30 phage had low sequence similarity compared to other phages infecting lactic acid bacteria. This is the first report of the morphological features and complete genome sequence of WCP30 phage, which may be useful for controlling the fermentation of dairy foods.

Incidental and clinically actionable genetic variants in 1005 whole exomes and genomes from Qatar

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Abhinav Jain

2017-10-01

Full Text Available Next generation sequencing (NGS technologies such as whole genome and whole exome sequencing has enabled accurate diagnosis of genetic diseases through identification of variations at the genome wide level. While many large populations have been adequately covered in global sequencing efforts little is known on the genomic architecture of populations from Middle East, and South Asia and Africa. Incidental findings and their prevalence in populations have been extensively studied in populations of Caucasian descent. The recent emphasis on genomics and availability of genome-scale datasets in public domain for ethnic population in the Middle East prompted us to estimate the prevalence of incidental findings for this population. In this study, we used whole genome and exome data for a total 1005 non-related healthy individuals from Qatar population dataset which contained 20,930,177 variants. Systematic analysis of the variants in 59 genes recommended by the American College of Medical Genetics and Genomics for reporting of incidental findings revealed a total of 2 pathogenic and 2 likely pathogenic variants. Our analysis suggests the prevalence of incidental variants in population-scale datasets is approx. 0.6%, much lower than those reported for global populations. Our study underlines the essentiality to study population-scale genomes from ethnic groups to understand systematic differences in genetic variants associated with disease predisposition.

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

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

OpenAIRE

Enyenihi, Akon H; Saunders, William S

2003-01-01

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

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

KAUST Repository

Hefzi, Hooman

2016-11-23

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

Analysis tools for the interplay between genome layout and regulation.

Science.gov (United States)

Bouyioukos, Costas; Elati, Mohamed; Képès, François

2016-06-06

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

Meta-analysis of 32 genome-wide linkage studies of schizophrenia

Science.gov (United States)

Ng, MYM; Levinson, DF; Faraone, SV; Suarez, BK; DeLisi, LE; Arinami, T; Riley, B; Paunio, T; Pulver, AE; Irmansyah; Holmans, PA; Escamilla, M; Wildenauer, DB; Williams, NM; Laurent, C; Mowry, BJ; Brzustowicz, LM; Maziade, M; Sklar, P; Garver, DL; Abecasis, GR; Lerer, B; Fallin, MD; Gurling, HMD; Gejman, PV; Lindholm, E; Moises, HW; Byerley, W; Wijsman, EM; Forabosco, P; Tsuang, MT; Hwu, H-G; Okazaki, Y; Kendler, KS; Wormley, B; Fanous, A; Walsh, D; O’Neill, FA; Peltonen, L; Nestadt, G; Lasseter, VK; Liang, KY; Papadimitriou, GM; Dikeos, DG; Schwab, SG; Owen, MJ; O’Donovan, MC; Norton, N; Hare, E; Raventos, H; Nicolini, H; Albus, M; Maier, W; Nimgaonkar, VL; Terenius, L; Mallet, J; Jay, M; Godard, S; Nertney, D; Alexander, M; Crowe, RR; Silverman, JM; Bassett, AS; Roy, M-A; Mérette, C; Pato, CN; Pato, MT; Roos, J Louw; Kohn, Y; Amann-Zalcenstein, D; Kalsi, G; McQuillin, A; Curtis, D; Brynjolfson, J; Sigmundsson, T; Petursson, H; Sanders, AR; Duan, J; Jazin, E; Myles-Worsley, M; Karayiorgou, M; Lewis, CM

2009-01-01

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (PSR) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for ‘aggregate’ genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies. PMID:19349958

Data analysis in the post-genome-wide association study era

Directory of Open Access Journals (Sweden)

Qiao-Ling Wang

2016-12-01

Full Text Available Since the first report of a genome-wide association study (GWAS on human age-related macular degeneration, GWAS has successfully been used to discover genetic variants for a variety of complex human diseases and/or traits, and thousands of associated loci have been identified. However, the underlying mechanisms for these loci remain largely unknown. To make these GWAS findings more useful, it is necessary to perform in-depth data mining. The data analysis in the post-GWAS era will include the following aspects: fine-mapping of susceptibility regions to identify susceptibility genes for elucidating the biological mechanism of action; joint analysis of susceptibility genes in different diseases; integration of GWAS, transcriptome, and epigenetic data to analyze expression and methylation quantitative trait loci at the whole-genome level, and find single-nucleotide polymorphisms that influence gene expression and DNA methylation; genome-wide association analysis of disease-related DNA copy number variations. Applying these strategies and methods will serve to strengthen GWAS data to enhance the utility and significance of GWAS in improving understanding of the genetics of complex diseases or traits and translate these findings for clinical applications. Keywords: Genome-wide association study, Data mining, Integrative data analysis, Polymorphism, Copy number variation

Be-Breeder - an application for analysis of genomic data in plant breeding

OpenAIRE

Matias,Filipe Inácio; Granato,Italo Stefanine Correa; Dequigiovanni,Gabriel; Fritsche-Neto,Roberto

2017-01-01

Abstract Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker) analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genome selection, genome association, and genetic diversity in a simple manner on line. ...

The Functional Genomics Initiative at Oak Ridge National Laboratory

Energy Technology Data Exchange (ETDEWEB)

Johnson, Dabney; Justice, Monica; Beattle, Ken; Buchanan, Michelle; Ramsey, Michael; Ramsey, Rose; Paulus, Michael; Ericson, Nance; Allison, David; Kress, Reid; Mural, Richard; Uberbacher, Ed; Mann, Reinhold

1997-12-31

The Functional Genomics Initiative at the Oak Ridge National Laboratory integrates outstanding capabilities in mouse genetics, bioinformatics, and instrumentation. The 50 year investment by the DOE in mouse genetics/mutagenesis has created a one-of-a-kind resource for generating mutations and understanding their biological consequences. It is generally accepted that, through the mouse as a surrogate for human biology, we will come to understand the function of human genes. In addition to this world class program in mammalian genetics, ORNL has also been a world leader in developing bioinformatics tools for the analysis, management and visualization of genomic data. Combining this expertise with new instrumentation technologies will provide a unique capability to understand the consequences of mutations in the mouse at both the organism and molecular levels. The goal of the Functional Genomics Initiative is to develop the technology and methodology necessary to understand gene function on a genomic scale and apply these technologies to megabase regions of the human genome. The effort is scoped so as to create an effective and powerful resource for functional genomics. ORNL is partnering with the Joint Genome Institute and other large scale sequencing centers to sequence several multimegabase regions of both human and mouse genomic DNA, to identify all the genes in these regions, and to conduct fundamental surveys to examine gene function at the molecular and organism level. The Initiative is designed to be a pilot for larger scale deployment in the post-genome era. Technologies will be applied to the examination of gene expression and regulation, metabolism, gene networks, physiology and development.

The large-scale blast score ratio (LS-BSR pipeline: a method to rapidly compare genetic content between bacterial genomes

Directory of Open Access Journals (Sweden)

Jason W. Sahl

2014-04-01

Full Text Available Background. As whole genome sequence data from bacterial isolates becomes cheaper to generate, computational methods are needed to correlate sequence data with biological observations. Here we present the large-scale BLAST score ratio (LS-BSR pipeline, which rapidly compares the genetic content of hundreds to thousands of bacterial genomes, and returns a matrix that describes the relatedness of all coding sequences (CDSs in all genomes surveyed. This matrix can be easily parsed in order to identify genetic relationships between bacterial genomes. Although pipelines have been published that group peptides by sequence similarity, no other software performs the rapid, large-scale, full-genome comparative analyses carried out by LS-BSR.Results. To demonstrate the utility of the method, the LS-BSR pipeline was tested on 96 Escherichia coli and Shigella genomes; the pipeline ran in 163 min using 16 processors, which is a greater than 7-fold speedup compared to using a single processor. The BSR values for each CDS, which indicate a relative level of relatedness, were then mapped to each genome on an independent core genome single nucleotide polymorphism (SNP based phylogeny. Comparisons were then used to identify clade specific CDS markers and validate the LS-BSR pipeline based on molecular markers that delineate between classical E. coli pathogenic variant (pathovar designations. Scalability tests demonstrated that the LS-BSR pipeline can process 1,000 E. coli genomes in 27–57 h, depending upon the alignment method, using 16 processors.Conclusions. LS-BSR is an open-source, parallel implementation of the BSR algorithm, enabling rapid comparison of the genetic content of large numbers of genomes. The results of the pipeline can be used to identify specific markers between user-defined phylogenetic groups, and to identify the loss and/or acquisition of genetic information between bacterial isolates. Taxa-specific genetic markers can then be translated

Quantitative high-resolution genomic analysis of single cancer cells.

Directory of Open Access Journals (Sweden)

Juliane Hannemann

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

Transcriptome analysis reveals the time of the fourth round of genome duplication in common carp (Cyprinus carpio)

Science.gov (United States)

2012-01-01

Background Common carp (Cyprinus carpio) is thought to have undergone one extra round of genome duplication compared to zebrafish. Transcriptome analysis has been used to study the existence and timing of genome duplication in species for which genome sequences are incomplete. Large-scale transcriptome data for the common carp genome should help reveal the timing of the additional duplication event. Results We have sequenced the transcriptome of common carp using 454 pyrosequencing. After assembling the 454 contigs and the published common carp sequences together, we obtained 49,669 contigs and identified genes using homology searches and an ab initio method. We identified 4,651 orthologous pairs between common carp and zebrafish and found 129,984 paralogous pairs within the common carp. An estimation of the synonymous substitution rate in the orthologous pairs indicated that common carp and zebrafish diverged 120 million years ago (MYA). We identified one round of genome duplication in common carp and estimated that it had occurred 5.6 to 11.3 MYA. In zebrafish, no genome duplication event after speciation was observed, suggesting that, compared to zebrafish, common carp had undergone an additional genome duplication event. We annotated the common carp contigs with Gene Ontology terms and KEGG pathways. Compared with zebrafish gene annotations, we found that a set of biological processes and pathways were enriched in common carp. Conclusions The assembled contigs helped us to estimate the time of the fourth-round of genome duplication in common carp. The resource that we have built as part of this study will help advance functional genomics and genome annotation studies in the future. PMID:22424280

BioNano genome mapping of individual chromosomes supports physical mapping and sequence assembly in complex plant genomes.

Science.gov (United States)

Staňková, Helena; Hastie, Alex R; Chan, Saki; Vrána, Jan; Tulpová, Zuzana; Kubaláková, Marie; Visendi, Paul; Hayashi, Satomi; Luo, Mingcheng; Batley, Jacqueline; Edwards, David; Doležel, Jaroslav; Šimková, Hana

2016-07-01

The assembly of a reference genome sequence of bread wheat is challenging due to its specific features such as the genome size of 17 Gbp, polyploid nature and prevalence of repetitive sequences. BAC-by-BAC sequencing based on chromosomal physical maps, adopted by the International Wheat Genome Sequencing Consortium as the key strategy, reduces problems caused by the genome complexity and polyploidy, but the repeat content still hampers the sequence assembly. Availability of a high-resolution genomic map to guide sequence scaffolding and validate physical map and sequence assemblies would be highly beneficial to obtaining an accurate and complete genome sequence. Here, we chose the short arm of chromosome 7D (7DS) as a model to demonstrate for the first time that it is possible to couple chromosome flow sorting with genome mapping in nanochannel arrays and create a de novo genome map of a wheat chromosome. We constructed a high-resolution chromosome map composed of 371 contigs with an N50 of 1.3 Mb. Long DNA molecules achieved by our approach facilitated chromosome-scale analysis of repetitive sequences and revealed a ~800-kb array of tandem repeats intractable to current DNA sequencing technologies. Anchoring 7DS sequence assemblies obtained by clone-by-clone sequencing to the 7DS genome map provided a valuable tool to improve the BAC-contig physical map and validate sequence assembly on a chromosome-arm scale. Our results indicate that creating genome maps for the whole wheat genome in a chromosome-by-chromosome manner is feasible and that they will be an affordable tool to support the production of improved pseudomolecules. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

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.

Oncogenomic portals for the visualization and analysis of genome-wide cancer data.

Science.gov (United States)

Klonowska, Katarzyna; Czubak, Karol; Wojciechowska, Marzena; Handschuh, Luiza; Zmienko, Agnieszka; Figlerowicz, Marek; Dams-Kozlowska, Hanna; Kozlowski, Piotr

2016-01-05

Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice.

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

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Wenbo Tang

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

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

Science.gov (United States)

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

2011-01-12

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

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

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Velasco Riccardo

2011-01-01

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

Analysis of radiation-induced genome alterations in Vigna unguiculata

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van der Vyver C

2011-09-01

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

Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments

Science.gov (United States)

2014-01-01

Background Whole-genome bisulfite sequencing currently provides the highest-precision view of the epigenome, with quantitative information about populations of cells down to single nucleotide resolution. Several studies have demonstrated the value of this precision: meaningful features that correlate strongly with biological functions can be found associated with only a few CpG sites. Understanding the role of DNA methylation, and more broadly the role of DNA accessibility, requires that methylation differences between populations of cells are identified with extreme precision and in complex experimental designs. Results In this work we investigated the use of beta-binomial regression as a general approach for modeling whole-genome bisulfite data to identify differentially methylated sites and genomic intervals. Conclusions The regression-based analysis can handle medium- and large-scale experiments where it becomes critical to accurately model variation in methylation levels between replicates and account for influence of various experimental factors like cell types or batch effects. PMID:24962134

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

Science.gov (United States)

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

2000-12-15

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

Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.

Science.gov (United States)

Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup

2011-09-01

The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.

Comparative genomic analysis of multidrug-resistant Streptococcus pneumoniae isolates

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Pan F

2018-05-01

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

Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

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Bharat Manna

2017-10-01

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

NeisseriaBase: a specialised Neisseria genomic resource and analysis platform.

Science.gov (United States)

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

2016-01-01

Database (VFDB) specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genome Comparison tool (PGC) for comparative genomic analysis and the Pathogenomics Profiling Tool (PathoProT) for the comparative pathogenomics analysis of Neisseria strains. Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at http://neisseria.um.edu.my.

NeisseriaBase: a specialised Neisseria genomic resource and analysis platform

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Wenning Zheng

2016-03-01

Factor Database (VFDB specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genome Comparison tool (PGC for comparative genomic analysis and the Pathogenomics Profiling Tool (PathoProT for the comparative pathogenomics analysis of Neisseria strains. Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at http://neisseria.um.edu.my.

In Depth Characterization of Repetitive DNA in 23 Plant Genomes Reveals Sources of Genome Size Variation in the Legume Tribe Fabeae.

Science.gov (United States)

Macas, Jiří; Novák, Petr; Pellicer, Jaume; Čížková, Jana; Koblížková, Andrea; Neumann, Pavel; Fuková, Iva; Doležel, Jaroslav; Kelly, Laura J; Leitch, Ilia J

2015-01-01

The differential accumulation and elimination of repetitive DNA are key drivers of genome size variation in flowering plants, yet there have been few studies which have analysed how different types of repeats in related species contribute to genome size evolution within a phylogenetic context. This question is addressed here by conducting large-scale comparative analysis of repeats in 23 species from four genera of the monophyletic legume tribe Fabeae, representing a 7.6-fold variation in genome size. Phylogenetic analysis and genome size reconstruction revealed that this diversity arose from genome size expansions and contractions in different lineages during the evolution of Fabeae. Employing a combination of low-pass genome sequencing with novel bioinformatic approaches resulted in identification and quantification of repeats making up 55-83% of the investigated genomes. In turn, this enabled an analysis of how each major repeat type contributed to the genome size variation encountered. Differential accumulation of repetitive DNA was found to account for 85% of the genome size differences between the species, and most (57%) of this variation was found to be driven by a single lineage of Ty3/gypsy LTR-retrotransposons, the Ogre elements. Although the amounts of several other lineages of LTR-retrotransposons and the total amount of satellite DNA were also positively correlated with genome size, their contributions to genome size variation were much smaller (up to 6%). Repeat analysis within a phylogenetic framework also revealed profound differences in the extent of sequence conservation between different repeat types across Fabeae. In addition to these findings, the study has provided a proof of concept for the approach combining recent developments in sequencing and bioinformatics to perform comparative analyses of repetitive DNAs in a large number of non-model species without the need to assemble their genomes.

In Depth Characterization of Repetitive DNA in 23 Plant Genomes Reveals Sources of Genome Size Variation in the Legume Tribe Fabeae.

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Jiří Macas

Full Text Available The differential accumulation and elimination of repetitive DNA are key drivers of genome size variation in flowering plants, yet there have been few studies which have analysed how different types of repeats in related species contribute to genome size evolution within a phylogenetic context. This question is addressed here by conducting large-scale comparative analysis of repeats in 23 species from four genera of the monophyletic legume tribe Fabeae, representing a 7.6-fold variation in genome size. Phylogenetic analysis and genome size reconstruction revealed that this diversity arose from genome size expansions and contractions in different lineages during the evolution of Fabeae. Employing a combination of low-pass genome sequencing with novel bioinformatic approaches resulted in identification and quantification of repeats making up 55-83% of the investigated genomes. In turn, this enabled an analysis of how each major repeat type contributed to the genome size variation encountered. Differential accumulation of repetitive DNA was found to account for 85% of the genome size differences between the species, and most (57% of this variation was found to be driven by a single lineage of Ty3/gypsy LTR-retrotransposons, the Ogre elements. Although the amounts of several other lineages of LTR-retrotransposons and the total amount of satellite DNA were also positively correlated with genome size, their contributions to genome size variation were much smaller (up to 6%. Repeat analysis within a phylogenetic framework also revealed profound differences in the extent of sequence conservation between different repeat types across Fabeae. In addition to these findings, the study has provided a proof of concept for the approach combining recent developments in sequencing and bioinformatics to perform comparative analyses of repetitive DNAs in a large number of non-model species without the need to assemble their genomes.

Meta-analysis of Genome-Wide Association Studies for Extraversion

DEFF Research Database (Denmark)

van den Berg, Stéphanie M; de Moor, Marleen H M; Verweij, K. J. H.

2016-01-01

small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found...... at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero...

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

A gene-based linkage map for Bicyclus anynana butterflies allows for a comprehensive analysis of synteny with the lepidopteran reference genome.

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Patrícia Beldade

2009-02-01

Full Text Available Lepidopterans (butterflies and moths are a rich and diverse order of insects, which, despite their economic impact and unusual biological properties, are relatively underrepresented in terms of genomic resources. The genome of the silkworm Bombyx mori has been fully sequenced, but comparative lepidopteran genomics has been hampered by the scarcity of information for other species. This is especially striking for butterflies, even though they have diverse and derived phenotypes (such as color vision and wing color patterns and are considered prime models for the evolutionary and developmental analysis of ecologically relevant, complex traits. We focus on Bicyclus anynana butterflies, a laboratory system for studying the diversification of novelties and serially repeated traits. With a panel of 12 small families and a biphasic mapping approach, we first assigned 508 expressed genes to segregation groups and then ordered 297 of them within individual linkage groups. We also coarsely mapped seven color pattern loci. This is the richest gene-based map available for any butterfly species and allowed for a broad-coverage analysis of synteny with the lepidopteran reference genome. Based on 462 pairs of mapped orthologous markers in Bi. anynana and Bo. mori, we observed strong conservation of gene assignment to chromosomes, but also evidence for numerous large- and small-scale chromosomal rearrangements. With gene collections growing for a variety of target organisms, the ability to place those genes in their proper genomic context is paramount. Methods to map expressed genes and to compare maps with relevant model systems are crucial to extend genomic-level analysis outside classical model species. Maps with gene-based markers are useful for comparative genomics and to resolve mapped genomic regions to a tractable number of candidate genes, especially if there is synteny with related model species. This is discussed in relation to the identification of

SOLiD sequencing of four Vibrio vulnificus genomes enables comparative genomic analysis and identification of candidate clade-specific virulence genes

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Telonis-Scott Marina

2010-09-01

Full Text Available Abstract Background Vibrio vulnificus is the leading cause of reported death from consumption of seafood in the United States. Despite several decades of research on molecular pathogenesis, much remains to be learned about the mechanisms of virulence of this opportunistic bacterial pathogen. The two complete and annotated genomic DNA sequences of V. vulnificus belong to strains of clade 2, which is the predominant clade among clinical strains. Clade 2 strains generally possess higher virulence potential in animal models of disease compared with clade 1, which predominates among environmental strains. SOLiD sequencing of four V. vulnificus strains representing different clades (1 and 2 and biotypes (1 and 2 was used for comparative genomic analysis. Results Greater than 4,100,000 bases were sequenced of each strain, yielding approximately 100-fold coverage for each of the four genomes. Although the read lengths of SOLiD genomic sequencing were only 35 nt, we were able to make significant conclusions about the unique and shared sequences among the genomes, including identification of single nucleotide polymorphisms. Comparative analysis of the newly sequenced genomes to the existing reference genomes enabled the identification of 3,459 core V. vulnificus genes shared among all six strains and 80 clade 2-specific genes. We identified 523,161 SNPs among the six genomes. Conclusions We were able to glean much information about the genomic content of each strain using next generation sequencing. Flp pili, GGDEF proteins, and genomic island XII were identified as possible virulence factors because of their presence in virulent sequenced strains. Genomic comparisons also point toward the involvement of sialic acid catabolism in pathogenesis.

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

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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

Genomics: Looking at Life in New Ways

Energy Technology Data Exchange (ETDEWEB)

Adams, Mark D. (Case-Western Reserve University)

2003-10-22

The availability of complete or nearly complete mouse, human, and rat genomes (in addition to those from many other species) has resulted in a series of new and powerful opportunities to apply the technologies and approaches developed for large-scale genome sequencing to the study of disease. New approaches to biological problems are being explored that involve concepts from computer science such as systems theory and modern large scale computing techniques. A recent project at Celera Genomics involved sequencing protein coding regions from several humans and a chimpanzee. Computational models of evolutionary divergence enabled us to identify genes with unique evolutionary signatures. These genes give us some insight into features that may be uniquely human. The laboratory mouse and rat have long been favorite mammalian models of human disease. Integrated approaches to the study of disease that combine genetics, DNA sequence analysis, and careful analysis of phenotype at a molecular level are becoming more common and powerful. In addition, evaluation of the variation inherent in normal populations is now being used to build networks to describe heart function based on the interaction of multiple phenotypes in randomized populations using a factorial design.

The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

DEFF Research Database (Denmark)

Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin

2015-01-01

DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

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.

Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats.

Science.gov (United States)

Nazaripanah, N; Adelirad, F; Delbari, A; Sahaf, R; Abbasi-Asl, T; Ohadi, M

2018-04-05

While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution. Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

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

Science.gov (United States)

Tajparast, Mohammad; Frigon, Dominic

2018-01-01

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

The Integrated Microbial Genomes (IMG) System: An Expanding Comparative Analysis Resource

Energy Technology Data Exchange (ETDEWEB)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Anderson, Iain; Lykidis, Athanasios; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

2009-09-13

The integrated microbial genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG contains both draft and complete microbial genomes integrated with other publicly available genomes from all three domains of life, together with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. Since its first release in 2005, IMG's data content and analytical capabilities have been constantly expanded through regular releases. Several companion IMG systems have been set up in order to serve domain specific needs, such as expert review of genome annotations. IMG is available at .

A universal genomic coordinate translator for comparative genomics.

Science.gov (United States)

Zamani, Neda; Sundström, Görel; Meadows, Jennifer R S; Höppner, Marc P; Dainat, Jacques; Lantz, Henrik; Haas, Brian J; Grabherr, Manfred G

2014-06-30

Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N2 with the number of available genomes, N. Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across

Third International E. coli genome meeting

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-12-31

Proceedings of the Third E. Coli Genome Meeting are provided. Presentations were divided into sessions entitled (1) Large Scale Sequencing, Sequence Analysis; (2) Databases; (3) Sequence Analysis; (4) Sequence Divergence in E. coli Strains; (5) Repeated Sequences and Regulatory Motifs; (6) Mutations, Rearrangements and Stress Responses; and (7) Origins of New Genes. The document provides a collection of abstracts of oral and poster presentations.

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

DEFF Research Database (Denmark)

Stark, Alexander; Lin, Michael F; Kheradpour, Pouya

2007-01-01

Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional e...... individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies....

The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows.

Science.gov (United States)

O'Connor, Brian D; Yuen, Denis; Chung, Vincent; Duncan, Andrew G; Liu, Xiang Kun; Patricia, Janice; Paten, Benedict; Stein, Lincoln; Ferretti, Vincent

2017-01-01

As genomic datasets continue to grow, the feasibility of downloading data to a local organization and running analysis on a traditional compute environment is becoming increasingly problematic. Current large-scale projects, such as the ICGC PanCancer Analysis of Whole Genomes (PCAWG), the Data Platform for the U.S. Precision Medicine Initiative, and the NIH Big Data to Knowledge Center for Translational Genomics, are using cloud-based infrastructure to both host and perform analysis across large data sets. In PCAWG, over 5,800 whole human genomes were aligned and variant called across 14 cloud and HPC environments; the processed data was then made available on the cloud for further analysis and sharing. If run locally, an operation at this scale would have monopolized a typical academic data centre for many months, and would have presented major challenges for data storage and distribution. However, this scale is increasingly typical for genomics projects and necessitates a rethink of how analytical tools are packaged and moved to the data. For PCAWG, we embraced the use of highly portable Docker images for encapsulating and sharing complex alignment and variant calling workflows across highly variable environments. While successful, this endeavor revealed a limitation in Docker containers, namely the lack of a standardized way to describe and execute the tools encapsulated inside the container. As a result, we created the Dockstore ( https://dockstore.org), a project that brings together Docker images with standardized, machine-readable ways of describing and running the tools contained within. This service greatly improves the sharing and reuse of genomics tools and promotes interoperability with similar projects through emerging web service standards developed by the Global Alliance for Genomics and Health (GA4GH).

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-03-16

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

pico-PLAZA, a genome database of microbial photosynthetic eukaryotes.

Science.gov (United States)

Vandepoele, Klaas; Van Bel, Michiel; Richard, Guilhem; Van Landeghem, Sofie; Verhelst, Bram; Moreau, Hervé; Van de Peer, Yves; Grimsley, Nigel; Piganeau, Gwenael

2013-08-01

With the advent of next generation genome sequencing, the number of sequenced algal genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse individual genome sequences, exploring complete genome information from multiple species for the analysis of user-defined sequences or gene lists remains a major challenge. pico-PLAZA is a web-based resource (http://bioinformatics.psb.ugent.be/pico-plaza/) for algal genomics that combines different data types with intuitive tools to explore genomic diversity, perform integrative evolutionary sequence analysis and study gene functions. Apart from homologous gene families, multiple sequence alignments, phylogenetic trees, Gene Ontology, InterPro and text-mining functional annotations, different interactive viewers are available to study genome organization using gene collinearity and synteny information. Different search functions, documentation pages, export functions and an extensive glossary are available to guide non-expert scientists. To illustrate the versatility of the platform, different case studies are presented demonstrating how pico-PLAZA can be used to functionally characterize large-scale EST/RNA-Seq data sets and to perform environmental genomics. Functional enrichments analysis of 16 Phaeodactylum tricornutum transcriptome libraries offers a molecular view on diatom adaptation to different environments of ecological relevance. Furthermore, we show how complementary genomic data sources can easily be combined to identify marker genes to study the diversity and distribution of algal species, for example in metagenomes, or to quantify intraspecific diversity from environmental strains. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Ten years of maintaining and expanding a microbial genome and metagenome analysis system.

Science.gov (United States)

Markowitz, Victor M; Chen, I-Min A; Chu, Ken; Pati, Amrita; Ivanova, Natalia N; Kyrpides, Nikos C

2015-11-01

Launched in March 2005, the Integrated Microbial Genomes (IMG) system is a comprehensive data management system that supports multidimensional comparative analysis of genomic data. At the core of the IMG system is a data warehouse that contains genome and metagenome datasets sequenced at the Joint Genome Institute or provided by scientific users, as well as public genome datasets available at the National Center for Biotechnology Information Genbank sequence data archive. Genomes and metagenome datasets are processed using IMG's microbial genome and metagenome sequence data processing pipelines and are integrated into the data warehouse using IMG's data integration toolkits. Microbial genome and metagenome application specific data marts and user interfaces provide access to different subsets of IMG's data and analysis toolkits. This review article revisits IMG's original aims, highlights key milestones reached by the system during the past 10 years, and discusses the main challenges faced by a rapidly expanding system, in particular the complexity of maintaining such a system in an academic setting with limited budgets and computing and data management infrastructure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

Science.gov (United States)

2012-01-01

Background Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. Results Here we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype). Conclusion This study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data. PMID:22631437

BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment

Science.gov (United States)

Boel, Annekatrien; Steyaert, Woutert; De Rocker, Nina; Menten, Björn; Callewaert, Bert; De Paepe, Anne; Coucke, Paul; Willaert, Andy

2016-01-01

Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from https://github.com/WouterSteyaert/BATCH-GE.git. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome. PMID:27461955

Comparative genomic analysis of single-molecule sequencing and hybrid approaches for finishing the Clostridium autoethanogenum JA1-1 strain DSM 10061 genome

Energy Technology Data Exchange (ETDEWEB)

Brown, Steven D [ORNL; Nagaraju, Shilpa [LanzaTech; Utturkar, Sagar M [ORNL; De Tissera, Sashini [LanzaTech; Segovia, Simón [LanzaTech; Mitchell, Wayne [LanzaTech; Land, Miriam L [ORNL; Dassanayake, Asela [LanzaTech; Köpke, Michael [LanzaTech

2014-01-01

Background Clostridium autoethanogenum strain JA1-1 (DSM 10061) is an acetogen capable of fermenting CO, CO2 and H2 (e.g. from syngas or waste gases) into biofuel ethanol and commodity chemicals such as 2,3-butanediol. A draft genome sequence consisting of 100 contigs has been published. Results A closed, high-quality genome sequence for C. autoethanogenum DSM10061 was generated using only the latest single-molecule DNA sequencing technology and without the need for manual finishing. It is assigned to the most complex genome classification based upon genome features such as repeats, prophage, nine copies of the rRNA gene operons. It has a low G + C content of 31.1%. Illumina, 454, Illumina/454 hybrid assemblies were generated and then compared to the draft and PacBio assemblies using summary statistics, CGAL, QUAST and REAPR bioinformatics tools and comparative genomic approaches. Assemblies based upon shorter read DNA technologies were confounded by the large number repeats and their size, which in the case of the rRNA gene operons were ~5 kb. CRISPR (Clustered Regularly Interspaced Short Paloindromic Repeats) systems among biotechnologically relevant Clostridia were classified and related to plasmid content and prophages. Potential associations between plasmid content and CRISPR systems may have implications for historical industrial scale Acetone-Butanol-Ethanol (ABE) fermentation failures and future large scale bacterial fermentations. While C. autoethanogenum contains an active CRISPR system, no such system is present in the closely related Clostridium ljungdahlii DSM 13528. A common prophage inserted into the Arg-tRNA shared between the strains suggests a common ancestor. However, C. ljungdahlii contains several additional putative prophages and it has more than double the amount of prophage DNA compared to C. autoethanogenum. Other differences include important metabolic genes for central metabolism (as an additional hydrogenase and the absence of a

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-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

Science.gov (United States)

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Genomic analysis and selected molecular pathways in rare cancers

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Sriram Chandrasekaran

2017-12-01

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

Genomics-enabled analysis of the emergent disease cotton bacterial blight.

Directory of Open Access Journals (Sweden)

Anne Z Phillips

2017-09-01

Full Text Available Cotton bacterial blight (CBB, an important disease of (Gossypium hirsutum in the early 20th century, had been controlled by resistant germplasm for over half a century. Recently, CBB re-emerged as an agronomic problem in the United States. Here, we report analysis of cotton variety planting statistics that indicate a steady increase in the percentage of susceptible cotton varieties grown each year since 2009. Phylogenetic analysis revealed that strains from the current outbreak cluster with race 18 Xanthomonas citri pv. malvacearum (Xcm strains. Illumina based draft genomes were generated for thirteen Xcm isolates and analyzed along with 4 previously published Xcm genomes. These genomes encode 24 conserved and nine variable type three effectors. Strains in the race 18 clade contain 3 to 5 more effectors than other Xcm strains. SMRT sequencing of two geographically and temporally diverse strains of Xcm yielded circular chromosomes and accompanying plasmids. These genomes encode eight and thirteen distinct transcription activator-like effector genes. RNA-sequencing revealed 52 genes induced within two cotton cultivars by both tested Xcm strains. This gene list includes a homeologous pair of genes, with homology to the known susceptibility gene, MLO. In contrast, the two strains of Xcm induce different clade III SWEET sugar transporters. Subsequent genome wide analysis revealed patterns in the overall expression of homeologous gene pairs in cotton after inoculation by Xcm. These data reveal important insights into the Xcm-G. hirsutum disease complex and strategies for future development of resistant cultivars.

Comparative mitochondrial genome analysis reveals the evolutionary rearrangement mechanism in Brassica.

Science.gov (United States)

Yang, J; Liu, G; Zhao, N; Chen, S; Liu, D; Ma, W; Hu, Z; Zhang, M

2016-05-01

The genus Brassica has many species that are important for oil, vegetable and other food products. Three mitochondrial genome types (mitotype) originated from its common ancestor. In this paper, a B. nigra mitochondrial main circle genome with 232,407 bp was generated through de novo assembly. Synteny analysis showed that the mitochondrial genomes of B. rapa and B. oleracea had a better syntenic relationship than B. nigra. Principal components analysis and development of a phylogenetic tree indicated maternal ancestors of three allotetraploid species in Us triangle of Brassica. Diversified mitotypes were found in allotetraploid B. napus, in which napus-type B. napus was derived from B. oleracea, while polima-type B. napus was inherited from B. rapa. In addition, the mitochondrial genome of napus-type B. napus was closer to botrytis-type than capitata-type B. oleracea. The sub-stoichiometric shifting of several mitochondrial genes suggested that mitochondrial genome rearrangement underwent evolutionary selection during domestication and/or plant breeding. Our findings clarify the role of diploid species in the maternal origin of allotetraploid species in Brassica and suggest the possibility of breeding selection of the mitochondrial genome. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.

Analysis of high-identity segmental duplications in the grapevine genome

Directory of Open Access Journals (Sweden)

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.

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

Group sparse canonical correlation analysis for genomic data integration.

Science.gov (United States)

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

2013-08-12

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

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

African Journals Online (AJOL)

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

Detailed analysis of putative genes encoding small proteins in legume genomes

Directory of Open Access Journals (Sweden)

Gabriel eGuillén

2013-06-01

Full Text Available Diverse plant genome sequencing projects coupled with powerful bioinformatics tools have facilitated massive data analysis to construct specialized databases classified according to cellular function. However, there are still a considerable number of genes encoding proteins whose function has not yet been characterized. Included in this category are small proteins (SPs, 30-150 amino acids encoded by short open reading frames (sORFs. SPs play important roles in plant physiology, growth, and development. Unfortunately, protocols focused on the genome-wide identification and characterization of sORFs are scarce or remain poorly implemented. As a result, these genes are underrepresented in many genome annotations. In this work, we exploited publicly available genome sequences of Phaseolus vulgaris, Medicago truncatula, Glycine max and Lotus japonicus to analyze the abundance of annotated SPs in plant legumes. Our strategy to uncover bona fide sORFs at the genome level was centered in bioinformatics analysis of characteristics such as evidence of expression (transcription, presence of known protein regions or domains, and identification of orthologous genes in the genomes explored. We collected 6170, 10461, 30521, and 23599 putative sORFs from P. vulgaris, G. max, M. truncatula, and L. japonicus genomes, respectively. Expressed sequence tags (ESTs available in the DFCI Gene Index database provided evidence that ~one-third of the predicted legume sORFs are expressed. Most potential SPs have a counterpart in a different plant species and counterpart regions or domains in larger proteins. Potential functional sORFs were also classified according to a reduced set of GO categories, and the expression of 13 of them during P. vulgaris nodule ontogeny was confirmed by qPCR. This analysis provides a collection of sORFs that potentially encode for meaningful SPs, and offers the possibility of their further functional evaluation.

A genomic background based method for association analysis in related individuals.

Directory of Open Access Journals (Sweden)

Najaf Amin

Full Text Available BACKGROUND: Feasibility of genotyping of hundreds and thousands of single nucleotide polymorphisms (SNPs in thousands of study subjects have triggered the need for fast, powerful, and reliable methods for genome-wide association analysis. Here we consider a situation when study participants are genetically related (e.g. due to systematic sampling of families or because a study was performed in a genetically isolated population. Of the available methods that account for relatedness, the Measured Genotype (MG approach is considered the 'gold standard'. However, MG is not efficient with respect to time taken for the analysis of genome-wide data. In this context we proposed a fast two-step method called Genome-wide Association using Mixed Model and Regression (GRAMMAR for the analysis of pedigree-based quantitative traits. This method certainly overcomes the drawback of time limitation of the measured genotype (MG approach, but pays in power. One of the major drawbacks of both MG and GRAMMAR, is that they crucially depend on the availability of complete and correct pedigree data, which is rarely available. METHODOLOGY: In this study we first explore type 1 error and relative power of MG, GRAMMAR, and Genomic Control (GC approaches for genetic association analysis. Secondly, we propose an extension to GRAMMAR i.e. GRAMMAR-GC. Finally, we propose application of GRAMMAR-GC using the kinship matrix estimated through genomic marker data, instead of (possibly missing and/or incorrect genealogy. CONCLUSION: Through simulations we show that MG approach maintains high power across a range of heritabilities and possible pedigree structures, and always outperforms other contemporary methods. We also show that the power of our proposed GRAMMAR-GC approaches to that of the 'gold standard' MG for all models and pedigrees studied. We show that this method is both feasible and powerful and has correct type 1 error in the context of genome-wide association analysis

PGSB/MIPS PlantsDB Database Framework for the Integration and Analysis of Plant Genome Data.

Science.gov (United States)

Spannagl, Manuel; Nussbaumer, Thomas; Bader, Kai; Gundlach, Heidrun; Mayer, Klaus F X

2017-01-01

Plant Genome and Systems Biology (PGSB), formerly Munich Institute for Protein Sequences (MIPS) PlantsDB, is a database framework for the integration and analysis of plant genome data, developed and maintained for more than a decade now. Major components of that framework are genome databases and analysis resources focusing on individual (reference) genomes providing flexible and intuitive access to data. Another main focus is the integration of genomes from both model and crop plants to form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny). Data exchange and integrated search functionality with/over many plant genome databases is provided within the transPLANT project.

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling.

Science.gov (United States)

Yu, Jiyang; Silva, Jose; Califano, Andrea

2016-01-15

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives. Indeed, rigorous statistical analysis of high-throughput FG screening data remains challenging, particularly when integrative analyses are used to combine multiple sh/sgRNAs targeting the same gene in the library. We use large RNAi and CRISPR repositories that are publicly available to evaluate a novel meta-analysis approach for FG screens via Bayesian hierarchical modeling, Screening Bayesian Evaluation and Analysis Method (ScreenBEAM). Results from our analysis show that the proposed strategy, which seamlessly combines all available data, robustly outperforms classical algorithms developed for microarray data sets as well as recent approaches designed for next generation sequencing technologies. Remarkably, the ScreenBEAM algorithm works well even when the quality of FG screens is relatively low, which accounts for about 80-95% of the public datasets. R package and source code are available at: https://github.com/jyyu/ScreenBEAM. ac2248@columbia.edu, jose.silva@mssm.edu, yujiyang@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Analysis of chloroplast genomes and a supermatrix inform reclassification of the Rhodomelaceae (Rhodophyta).

Science.gov (United States)

Díaz-Tapia, Pilar; Maggs, Christine A; West, John A; Verbruggen, Heroen

2017-10-01

With over a thousand species, the Rhodomelaceae is the most species-rich family of red algae. While its genera have been assigned to 14 tribes, the high-level classification of the family has never been evaluated with a molecular phylogeny. Here, we reassess its classification by integrating genome-scale phylogenetic analysis with observations of the morphological characters of clades. In order to resolve relationships among the main lineages of the family we constructed a phylogeny with 55 chloroplast genomes (52 newly determined). The majority of branches were resolved with full bootstrap support. We then added 266 rbcL, 125 18S rRNA gene and 143 cox1 sequences to construct a comprehensive phylogeny containing nearly half of all known species in the family (407 species in 89 genera). These analyses suggest the same subdivision into higher-level lineages, but included many branches with moderate or poor support. The circumscription for nine of the 13 previously described tribes was supported, but the Lophothalieae, Polysiphonieae, Pterosiphonieae and Herposiphonieae required revision, and five new tribes and one resurrected tribe were segregated from them. Rhizoid anatomy is highlighted as a key diagnostic character for the morphological delineation of several lineages. This work provides the most extensive phylogenetic analysis of the Rhodomelaceae to date and successfully resolves the relationships among major clades of the family. Our data show that organellar genomes obtained through high-throughput sequencing produce well-resolved phylogenies of difficult groups, and their more general application in algal systematics will likely permit deciphering questions about classification at many taxonomic levels. © 2017 Phycological Society of America.

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

Science.gov (United States)

2016-03-15

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

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

Science.gov (United States)

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

2012-01-01

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

Proteinortho: Detection of (Co-)orthologs in large-scale analysis

OpenAIRE

Lechner, Marcus; Findeiß, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-01-01

Abstract Background Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes i...

SIDEKICK: Genomic data driven analysis and decision-making framework

Directory of Open Access Journals (Sweden)

Yoon Kihoon

2010-12-01

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

Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

Science.gov (United States)

Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

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

Directory of Open Access Journals (Sweden)

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.

Genome-wide analysis of EgEVE_1, a transcriptionally active endogenous viral element associated to small RNAs in Eucalyptus genomes

Directory of Open Access Journals (Sweden)

Helena Sanches Marcon

2017-02-01

Full Text Available Abstract Endogenous viral elements (EVEs are the result of heritable horizontal gene transfer from viruses to hosts. In the last years, several EVE integration events were reported in plants by the exponential availability of sequenced genomes. Eucalyptus grandis is a forest tree species with a sequenced genome that is poorly studied in terms of evolution and mobile genetic elements composition. Here we report the characterization of E. grandis endogenous viral element 1 (EgEVE_1, a transcriptionally active EVE with a size of 5,664 bp. Phylogenetic analysis and genomic distribution demonstrated that EgEVE_1 is a newly described member of the Caulimoviridae family, distinct from the recently characterized plant Florendoviruses. Genomic distribution of EgEVE_1 and Florendovirus is also distinct. EgEVE_1 qPCR quantification in Eucalyptus urophylla suggests that this genome has more EgEVE_1 copies than E. grandis. EgEVE_1 transcriptional activity was demonstrated by RT-qPCR in five Eucalyptus species and one intrageneric hybrid. We also identified that Eucalyptus EVEs can generate small RNAs (sRNAs,that might be involved in de novo DNA methylation and virus resistance. Our data suggest that EVE families in Eucalyptus have distinct properties, and we provide the first comparative analysis of EVEs in Eucalyptus genomes.

Intraspecific phylogenetic analysis of Siberian woolly mammoths using complete mitochondrial genomes

DEFF Research Database (Denmark)

Gilbert, M Thomas P; Drautz, Daniela I; Lesk, Arthur M

2008-01-01

We report five new complete mitochondrial DNA (mtDNA) genomes of Siberian woolly mammoth (Mammuthus primigenius), sequenced with up to 73-fold coverage from DNA extracted from hair shaft material. Three of the sequences present the first complete mtDNA genomes of mammoth clade II. Analysis...... to indicate any important functional difference between genomes belonging to the two clades, suggesting that the loss of clade II more likely is due to genetic drift than a selective sweep....

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.

Proteinortho: detection of (co-)orthologs in large-scale analysis.

Science.gov (United States)

Lechner, Marcus; Findeiss, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-04-28

Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

Proteinortho: Detection of (Co-orthologs in large-scale analysis

Directory of Open Access Journals (Sweden)

Steiner Lydia

2011-04-01

Full Text Available Abstract Background Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. Results The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Conclusions Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

Reconstruction of genome-scale human metabolic models using omics data

DEFF Research Database (Denmark)

Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

2015-01-01

used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

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

DEFF Research Database (Denmark)

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

2008-01-01

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

Prokaryote genome fluidity: toward a system approach of the mobilome.

Science.gov (United States)

Toussaint, Ariane; Chandler, Mick

2012-01-01

The importance of horizontal/lateral gene transfer (LGT) in shaping the genomes of prokaryotic organisms has been recognized in recent years as a result of analysis of the increasing number of available genome sequences. LGT is largely due to the transfer and recombination activities of mobile genetic elements (MGEs). Bacterial and archaeal genomes are mosaics of vertically and horizontally transmitted DNA segments. This generates reticulate relationships between members of the prokaryotic world that are better represented by networks than by "classical" phylogenetic trees. In this review we summarize the nature and activities of MGEs, and the problems that presently limit their analysis on a large scale. We propose routes to improve their annotation in the flow of genomic and metagenomic sequences that currently exist and those that become available. We describe network analysis of evolutionary relationships among some MGE categories and sketch out possible developments of this type of approach to get more insight into the role of the mobilome in bacterial adaptation and evolution.

Mycobacterial species as case-study of comparative genome analysis

DEFF Research Database (Denmark)

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

2011-01-01

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

Synonymous Codon Usage Analysis of Thirty Two Mycobacteriophage Genomes

Directory of Open Access Journals (Sweden)

Sameer Hassan

2009-01-01

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

Comparative analysis of the genomes of Stylophora pistillata and Acropora digitifera provides evidence for extensive differences between species of corals

KAUST Repository

Voolstra, Christian R.; Li, Yong; Liew, Yi Jin; Baumgarten, Sebastian; Zoccola, Didier; Flot, Jean-Franç ois; Tambutté , Sylvie; Allemand, Denis; Aranda, Manuel

2017-01-01

Stony corals form the foundation of coral reef ecosystems. Their phylogeny is characterized by a deep evolutionary divergence that separates corals into a robust and complex clade dating back to at least 245 mya. However, the genomic consequences and clade-specific evolution remain unexplored. In this study we have produced the genome of a robust coral, Stylophora pistillata, and compared it to the available genome of a complex coral, Acropora digitifera. We conducted a fine-scale gene-based analysis focusing on ortholog groups. Among the core set of conserved proteins, we found an emphasis on processes related to the cnidarian-dinoflagellate symbiosis. Genes associated with the algal symbiosis were also independently expanded in both species, but both corals diverged on the identity of ortholog groups expanded, and we found uneven expansions in genes associated with innate immunity and stress response. Our analyses demonstrate that coral genomes can be surprisingly disparate. Future analyses incorporating more genomic data should be able to determine whether the patterns elucidated here are not only characteristic of the differences between S. pistillata and A. digitifera but also representative of corals from the robust and complex clade at large.

Comparative analysis of the genomes of Stylophora pistillata and Acropora digitifera provides evidence for extensive differences between species of corals

KAUST Repository

Voolstra, Christian R.

2017-12-08

Stony corals form the foundation of coral reef ecosystems. Their phylogeny is characterized by a deep evolutionary divergence that separates corals into a robust and complex clade dating back to at least 245 mya. However, the genomic consequences and clade-specific evolution remain unexplored. In this study we have produced the genome of a robust coral, Stylophora pistillata, and compared it to the available genome of a complex coral, Acropora digitifera. We conducted a fine-scale gene-based analysis focusing on ortholog groups. Among the core set of conserved proteins, we found an emphasis on processes related to the cnidarian-dinoflagellate symbiosis. Genes associated with the algal symbiosis were also independently expanded in both species, but both corals diverged on the identity of ortholog groups expanded, and we found uneven expansions in genes associated with innate immunity and stress response. Our analyses demonstrate that coral genomes can be surprisingly disparate. Future analyses incorporating more genomic data should be able to determine whether the patterns elucidated here are not only characteristic of the differences between S. pistillata and A. digitifera but also representative of corals from the robust and complex clade at large.

A human genome-wide library of local phylogeny predictions for whole-genome inference problems

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Schwartz Russell

2008-08-01

Full Text Available Abstract Background Many common inference problems in computational genetics depend on inferring aspects of the evolutionary history of a data set given a set of observed modern sequences. Detailed predictions of the full phylogenies are therefore of value in improving our ability to make further inferences about population history and sources of genetic variation. Making phylogenetic predictions on the scale needed for whole-genome analysis is, however, extremely computationally demanding. Results In order to facilitate phylogeny-based predictions on a genomic scale, we develop a library of maximum parsimony phylogenies within local regions spanning all autosomal human chromosomes based on Haplotype Map variation data. We demonstrate the utility of this library for population genetic inferences by examining a tree statistic we call 'imperfection,' which measures the reuse of variant sites within a phylogeny. This statistic is significantly predictive of recombination rate, shows additional regional and population-specific conservation, and allows us to identify outlier genes likely to have experienced unusual amounts of variation in recent human history. Conclusion Recent theoretical advances in algorithms for phylogenetic tree reconstruction have made it possible to perform large-scale inferences of local maximum parsimony phylogenies from single nucleotide polymorphism (SNP data. As results from the imperfection statistic demonstrate, phylogeny predictions encode substantial information useful for detecting genomic features and population history. This data set should serve as a platform for many kinds of inferences one may wish to make about human population history and genetic variation.

2012 U.S. Department of Energy: Joint Genome Institute: Progress Report

Energy Technology Data Exchange (ETDEWEB)

Gilbert, David [DOE JGI Public Affairs Manager

2013-01-01

The mission of the U.S. Department of Energy Joint Genome Institute (DOE JGI) is to serve the diverse scientific community as a user facility, enabling the application of large-scale genomics and analysis of plants, microbes, and communities of microbes to address the DOE mission goals in bioenergy and the environment. The DOE JGI's sequencing efforts fall under the Eukaryote Super Program, which includes the Plant and Fungal Genomics Programs; and the Prokaryote Super Program, which includes the Microbial Genomics and Metagenomics Programs. In 2012, several projects made news for their contributions to energy and environment research.

An improved model for whole genome phylogenetic analysis by Fourier transform.

Science.gov (United States)

Yin, Changchuan; Yau, Stephen S-T

2015-10-07

DNA sequence similarity comparison is one of the major steps in computational phylogenetic studies. The sequence comparison of closely related DNA sequences and genomes is usually performed by multiple sequence alignments (MSA). While the MSA method is accurate for some types of sequences, it may produce incorrect results when DNA sequences undergone rearrangements as in many bacterial and viral genomes. It is also limited by its computational complexity for comparing large volumes of data. Previously, we proposed an alignment-free method that exploits the full information contents of DNA sequences by Discrete Fourier Transform (DFT), but still with some limitations. Here, we present a significantly improved method for the similarity comparison of DNA sequences by DFT. In this method, we map DNA sequences into 2-dimensional (2D) numerical sequences and then apply DFT to transform the 2D numerical sequences into frequency domain. In the 2D mapping, the nucleotide composition of a DNA sequence is a determinant factor and the 2D mapping reduces the nucleotide composition bias in distance measure, and thus improving the similarity measure of DNA sequences. To compare the DFT power spectra of DNA sequences with different lengths, we propose an improved even scaling algorithm to extend shorter DFT power spectra to the longest length of the underlying sequences. After the DFT power spectra are evenly scaled, the spectra are in the same dimensionality of the Fourier frequency space, then the Euclidean distances of full Fourier power spectra of the DNA sequences are used as the dissimilarity metrics. The improved DFT method, with increased computational performance by 2D numerical representation, can be applicable to any DNA sequences of different length ranges. We assess the accuracy of the improved DFT similarity measure in hierarchical clustering of different DNA sequences including simulated and real datasets. The method yields accurate and reliable phylogenetic trees

Analysis Of Segmental Duplications In The Pig Genome Based On Next-Generation Sequencing

DEFF Research Database (Denmark)

Fadista, João; Bendixen, Christian

Segmental duplications are >1kb segments of duplicated DNA present in a genome with high sequence identity (>90%). They are associated with genomic rearrangements and provide a significant source of gene and genome evolution within mammalian genomes. Although segmental duplications have been...... extensively studied in other organisms, its analysis in pig has been hampered by the lack of a complete pig genome assembly. By measuring the depth of coverage of Illumina whole-genome shotgun sequencing reads of the Tabasco animal aligned to the latest pig genome assembly (Sus scrofa 10 – based also...... and their associated copy number alterations, focusing on the global organization of these segments and their possible functional significance in porcine phenotypes. This work provides insights into mammalian genome evolution and generates a valuable resource for porcine genomics research...

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

Science.gov (United States)

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

2016-01-01

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

BGI-RIS: an integrated information resource and comparative analysis workbench for rice genomics

DEFF Research Database (Denmark)

Zhao, Wenming; Wang, Jing; He, Ximiao

2004-01-01

Rice is a major food staple for the world's population and serves as a model species in cereal genome research. The Beijing Genomics Institute (BGI) has long been devoting itself to sequencing, information analysis and biological research of the rice and other crop genomes. In order to facilitate....... Designed as a basic platform, BGI-RIS presents the sequenced genomes and related information in systematic and graphical ways for the convenience of in-depth comparative studies (http://rise.genomics.org.cn/). Udgivelsesdato: 2004-Jan-1...

Successful application of FTA Classic Card technology and use of bacteriophage phi29 DNA polymerase for large-scale field sampling and cloning of complete maize streak virus genomes.

Science.gov (United States)

Owor, Betty E; Shepherd, Dionne N; Taylor, Nigel J; Edema, Richard; Monjane, Adérito L; Thomson, Jennifer A; Martin, Darren P; Varsani, Arvind

2007-03-01

Leaf samples from 155 maize streak virus (MSV)-infected maize plants were collected from 155 farmers' fields in 23 districts in Uganda in May/June 2005 by leaf-pressing infected samples onto FTA Classic Cards. Viral DNA was successfully extracted from cards stored at room temperature for 9 months. The diversity of 127 MSV isolates was analysed by PCR-generated RFLPs. Six representative isolates having different RFLP patterns and causing either severe, moderate or mild disease symptoms, were chosen for amplification from FTA cards by bacteriophage phi29 DNA polymerase using the TempliPhi system. Full-length genomes were inserted into a cloning vector using a unique restriction enzyme site, and sequenced. The 1.3-kb PCR product amplified directly from FTA-eluted DNA and used for RFLP analysis was also cloned and sequenced. Comparison of cloned whole genome sequences with those of the original PCR products indicated that the correct virus genome had been cloned and that no errors were introduced by the phi29 polymerase. This is the first successful large-scale application of FTA card technology to the field, and illustrates the ease with which large numbers of infected samples can be collected and stored for downstream molecular applications such as diversity analysis and cloning of potentially new virus genomes.

Comparing Mycobacterium tuberculosis genomes using genome topology networks.

Science.gov (United States)

Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan

2015-02-14

Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes

Exploring Networks at the genome scale

NARCIS (Netherlands)

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

2010-01-01

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

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.

Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis.