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At least 289 records · Page 16Linked to original sources
PubMed1998

Escherichia coli molecular phylogeny using the incongruence length difference test.

Molecular phylogeny of the species Escherichia coli using the E. coli reference (ECOR) collection strains has been hampered by (1) the absence of rooting in the commonly used phenogram obtained from multilocus enzyme electrophoresis (MLEE) data and (2) the existence of recombination events between strains that scramble phylogenetic trees reconstructed from the nucleotide sequences of genes. We attempted to determine the phylogeny for E. coli based on the ECOR strain data by extracting from GenBank the nucleotide sequences of 11 chromosomal structural and 2 plasmid genes for which the Salmonella enterica homologous gene sequences were available. For each of the 13 DNA data sets studied, incongruence with a nonnucleotide whole-genome data set including MLEE, random amplified polymorphic DNA, and rrn restriction fragment length polymorphism data was measured using the incongruence length difference (ILD) test of Farris et al. As previously reported, the incongruence observed between the gnd and plasmid gene data and the whole-genome data was multiple, indicating numerous horizontal transfer and/or recombination events. In five cases, the incongruence detected by the ILD test was punctual, and the donor group was identified. Congruence was not rejected for the remaining data sets. The strains responsible for incongruences with the whole-genome data set were removed, leading to a "prior-agreement" approach, i.e., the determination of a phylogeny for E. coli based on several genes, excluding (1) the genes with multiple incongruences with the whole genome data, (2) the strains responsible for punctual incongruences, and (3) the genes incongruent with each other. The obtained phylogeny shows that the most basal group of E. coli strains is the B2 group rather than the A group, as generally thought. The D group then emerges as the sister group of the rest. Finally, the A and B1 groups are sister groups. Interestingly, the most primitive taxon within E. coli in terms of branching pattern, i.e., the B2 group, includes highly virulent extraintestinal strains with derived characters (extraintestinal virulence determinants) occurring on its own branch.

Enzymes↗
PubMed2004

Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.

The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

Animals↗
PubMed2001

Use of whole genome sequence data to infer baculovirus phylogeny.

Several phylogenetic methods based on whole genome sequence data were evaluated using data from nine complete baculovirus genomes. The utility of three independent character sets was assessed. The first data set comprised the sequences of the 63 genes common to these viruses. The second set of characters was based on gene order, and phylogenies were inferred using both breakpoint distance analysis and a novel method developed here, termed neighbor pair analysis. The third set recorded gene content by scoring gene presence or absence in each genome. All three data sets yielded phylogenies supporting the separation of the Nucleopolyhedrovirus (NPV) and Granulovirus (GV) genera, the division of the NPVs into groups I and II, and species relationships within group I NPVs. Generation of phylogenies based on the combined sequences of all 63 shared genes proved to be the most effective approach to resolving the relationships among the group II NPVs and the GVs. The history of gene acquisitions and losses that have accompanied baculovirus diversification was visualized by mapping the gene content data onto the phylogenetic tree. This analysis highlighted the fluid nature of baculovirus genomes, with evidence of frequent genome rearrangements and multiple gene content changes during their evolution. Of more than 416 genes identified in the genomes analyzed, only 63 are present in all nine genomes, and 200 genes are found only in a single genome. Despite this fluidity, the whole genome-based methods we describe are sufficiently powerful to recover the underlying phylogeny of the viruses.

Animals↗
PubMed2004

Ordered partitioning reveals extended splice-site consensus information.

Using recently available cDNA and genomic data (Berkeley Drosophila Genome Project; http://www.fruitfly.org), we computed a large sample of 10,057 Drosophila splice sites. An information-theoretic analysis of the nucleotide sequences adjacent to these splice sites showed a strong correlation between the sizes of introns and exons and the levels of information, which is a measure of sequence conservation. The strong correlation permitted us to determine extensive consensus sequences at the donor and acceptor sites of longer introns. These sequences were further refined and extended by examining the information in regions around splice sites that only partially matched the consensus. The correlation between length and information provided the basis for determining alternative consensus arrangements associated with shorter introns, as well as general base-composition preferences that likely promote spliceosome function. We also observed a correlation between information near splice sites and the lengths of nonadjacent introns, indicating that there are long-range effects spanning multiple introns. The ordered partitioning approach used in this analysis may become increasingly useful as large genomic data sets become available.

Animals↗
PubMed2002

Genome-tools: a flexible package for genome sequence analysis.

Genome-tools is a Perl module, a set of programs, and a user interface that facilitates access to genome sequence information. The package is flexible, extensible, and designed to be accessible and useful to both nonprogrammers and programmers. Any relatively well-annotated genome available with standard GenBank genome files may be used with genome-tools. A simple Web-based front end permits searching any available genome with an intuitive interface. Flexible design choices also make it simple to handle revised versions of genome annotation files as they change. In addition, programmers can develop cross-genomic tools and analyses with minimal additional overhead by combining genome-tools modules with newly written modules. Genome-tools runs on any computer platform for which Perl is available, including Unix, Microsoft Windows, and Mac OS. By simplifying the access to large amounts of genomic data, genome-tools may be especially useful for molecular biologists looking at newly sequenced genomes, for which few informatics tools are available. The genome-tools Web interface is accessible at http://genome-tools.sourceforge.net, and the source code is available at http://sourceforge.net/projects/genome-tools.

Base Sequence↗
PubMed2002

Context-specific Bayesian clustering for gene expression data.

The recent growth in genomic data and measurements of genome-wide expression patterns allows us to apply computational tools to examine gene regulation by transcription factors. In this work, we present a class of mathematical models that help in understanding the connections between transcription factors and functional classes of genes based on genetic and genomic data. Such a model represents the joint distribution of transcription factor binding sites and of expression levels of a gene in a unified probabilistic model. Learning a combined probability model of binding sites and expression patterns enables us to improve the clustering of the genes based on the discovery of putative binding sites and to detect which binding sites and experiments best characterize a cluster. To learn such models from data, we introduce a new search method that rapidly learns a model according to a Bayesian score. We evaluate our method on synthetic data as well as on real life data and analyze the biological insights it provides. Finally, we demonstrate the applicability of the method to other data analysis problems in gene expression data.

Bayes Theorem↗
PubMed2024

Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification.

The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a priori assigning isolates to lineages from phylogenies, based solely on the abundance of single nucleotide polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a priori assigning isolates to lineages.

COVID-19↗
PubMed2002

Genome size and the accumulation of simple sequence repeats: implications of new data from genome sequencing projects.

The relationship between the level of repetitiveness in genomic sequences and genome size has been re-investigated making use of the rapidly growing database of complete eubacterial and archaeal genome sequences combined with the fragmentary but now large amount of data from eukaryotic genomes. Relative simplicity factors (RSFs), which measure the repetitiveness of sequences, were calculated and significantly simple motifs (SSMs), which identify the kinds of sequences that are repeated, were identified. A previously reported correlation between genome size and repetitiveness was confirmed, but it was shown that the higher RSFs seen in eukaryotic genomes also reflect a generally higher level of repetitiveness independent of genome size differences. Differences in genome size are responsible for about 10% of the variance in RSF seen between species. The spectrum of SSMs seen within a genome differed markedly within the eubacteria but less so in eukaryotes and, particularly, in archaea. Species with SSM spectra that differ from the norm tend also to have high RSFs for their genome size and to be pathogens that make use of repetitive sequences to avoid host defence responses. Some of the variance in repetitiveness seen in other species may therefore also reflect the action of selection, although other forces such as variation in the effectiveness of mechanisms for regulating slippage errors of replication, may also be important.

Animals↗
PubMed2006

Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.

Animals↗
PubMed2026

Genome sequence data of the chitinase-producing bacterium Paenibacillus mucilaginosus YWY-5.1.

Paenibacillus mucilaginosus is a beneficial bacterium widely applied as a biofertilizer in agriculture. To date, genomic information on this species remains limited; however, no genome assemblies from Vietnam have been reported. This work presented the draft genome of P. mucilaginosus YWY-5.1, a promising strain with strong chitin-degrading capability and agricultural potential, isolated from Yok Don National Park, Vietnam, using Illumina technology. Results showed that the assembled genome comprised 48 contigs with 4,076,146 bp and 73.8% GC-content. Genome annotation identified 3,611 protein-coding genes, 2 rRNA genes, and 53 tRNA genes. A total of 150 carbohydrate-active enzyme-related genes were predicted from the genome; among them, seven putative chitinolytic genes were identified, including 4 genes related to family 18 chitinase, 2 genes to family 20 β-N-acetylglucosaminidase, and one gene to auxiliary activity family 10. In addition, at least 32 genes related to plant growth-promoting functions were identified, including those associated with indole-3-acetic acid production, phosphate and potassium solubilization, siderophore biosynthesis, iron uptake, ACC metabolism, and nitrate transport and reduction. Furthermore, genome mining identified 4 biosynthetic gene clusters probably involved in secondary metabolite production, of which 3 displayed no similarity to previously reported clusters, indicating potential for novel bioactive compounds. These genomic data improved our understanding of the biodegradation capacity and agricultural potential of P. mucilaginosus YWY-5.1 isolated from Vietnam, and provided a valuable genomic resource for future functional and biotechnological investigations toward crop production and related fields.

Chitinases↗
PubMed2004

Visualization and analysis of microarray and gene ontology data with treemaps.

BACKGROUND: The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data in the midst of discovery increase the challenge of integrating experimental results with information resources. The use of Gene Ontology enables researchers to summarize results of quantitative analyses in this framework, but the limitations of typical browser presentation restrict data access. RESULTS: Here we describe extensions to the treemap design to visualize and query genome data. Treemaps are a space-filling visualization technique for hierarchical structures that show attributes of leaf nodes by size and color-coding. Treemaps enable users to rapidly compare sizes of nodes and sub-trees, and we use Gene Ontology categories, levels of RNA, and other quantitative attributes of DNA microarray experiments as examples. Our implementation of treemaps, Treemap 4.0, allows user-defined filtering to focus on the data of greatest interest, and these queried files can be exported for secondary analyses. Links to model system web pages from Treemap 4.0 enable users access to details about specific genes without leaving the query platform. CONCLUSIONS: Treemaps allow users to view and query the data from an experiment on a single computer monitor screen. Treemap 4.0 can be used to visualize various genome data, and is particularly useful for revealing patterns and details within complex data sets.

Animals↗
PubMed2006

G-InforBIO: integrated system for microbial genomics.

BACKGROUND: Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs. RESULTS: The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses. CONCLUSION: The G-InforBIO system simplifies genome analyses by integrating several available software programs to allow efficient handling and manipulation of genome data. G-InforBIO is freely available from the download site.

Algorithms↗
PubMed2002

Comparative analysis of multiple genome-scale data sets.

The ongoing analyses of published genome-scale data sets is evidence that different approaches are required to completely mine this data. We report the use of novel tools for both visualization and data set comparison to analyze yeast gene-expression (cell cycle and exit from stationary phase/G(0)) and protein-interaction studies. This analysis led to new insights about each data set. For example, G(1)-regulated genes are not co-regulated during exit from stationary phase, indicating that the cells are not synchronized. The tight clustering of other genes during exit from stationary-phase data set further indicates the physiological responses during G(0) exit are separable from cell-cycle events. Comparison of the two data sets showed that ribosomal-protein genes cluster tightly during exit from stationary phase, but are found in three significantly different clusters in the cell-cycle data set. Two protein-interaction data sets were also compared with the gene-expression data. Visual analysis of the complete data sets showed no clear correlation between co-expression of genes and protein interactions, in contrast to published reports examining subsets of the protein-interaction data. Neither two-hybrid study identified a large number of interactions between ribosomal proteins, consistent with recent structural data, indicating that for both data sets, the identification of false-positive interactions may be lower than previously thought.

Cell Cycle↗
PubMed2006

GenRate: a generative model that reveals novel transcripts in genome-tiling microarray data.

Genome-wide microarray designs containing millions to hundreds of millions of probes are available for a variety of mammals, including mouse and human. These genome tiling arrays can potentially lead to significant advances in science and medicine, e.g., by indicating new genes and alternative primary and secondary transcripts. While bottom-up pattern matching techniques (e.g., hierarchical clustering) can be used to find gene structures in microarray data, we believe the many interacting hidden variables and complex noise patterns more naturally lead to an analysis based on generative models. We describe a generative model of tiling data and show how the sum-product algorithm can be used to infer hybridization noise, probe sensitivity, new transcripts, and alternative transcripts. The method, called GenRate, maximizes a global scoring function that enables multiple transcripts to compete for ownership of putative probes. We apply GenRate to a new exon tiling dataset from mouse chromosome 4 and show that it makes significantly more predictions than a previously described hierarchical clustering method at the same false positive rate. GenRate correctly predicts many known genes and also predicts new gene structures. As new problems arise, additional hidden variables can be incorporated into the model in a principled fashion, so we believe that GenRate will prove to be a useful tool in the new era of genome-wide tiling microarray analysis.

Animals↗
PubMed2003

Secure web book to store structural genomics research data.

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

Crystallography, X-Ray↗
PubMed2003

Characterisation of IS901 integration sites in the Mycobacterium avium genome.

Data are presented on the identification and characterisation of 17 chromosomal integration loci of the insertion element IS901 in the Mycobacterium avium (cervine strain JD88/118) genome. Thirteen of these integration loci have been mapped to their corresponding positions on the M. avium strain 104 (an IS901(-) strain) genome (The Institute for Genome Research (TIGR) unfinished genome-sequencing project). Sequence data for both upstream and downstream sequence flanking regions were obtained for 12 insertion loci, while upstream sequence was obtained for five others. A consensus IS901 insertion target sequence compiled from all 17 integration sites was in broad agreement with earlier reports that were based on only two such loci. Analysis of IS901 integration site flanking sequences revealed that, like IS900 in M. avium subspecies paratuberculosis, IS901 inserts preferentially between a putative ribosome-binding sequence (RBS) and the translational start codon of an open reading frame (ORF). In BLAST X and BLAST P searches of the GenBank database, these ORFs were shown to share significant homologies with a number of other prokaryotic genes.

3' Flanking Region↗
PubMed1997

Public informatics resources for rice and other grasses.

As an emerging model system, rice will benefit from an informatics infrastructure which organizes genome data and makes it available worldwide. RiceGenes and other Internet-accessible resources are evolving to meet these goals. Grass crops such as rice, maize, millet, sorghum and wheat are closely related but are represented by independent database projects; interlinking these resources would create a broad view of grass genetics and make it easier to compare data across genomes. The future success of grass informatics depends on the development of new comparative mapping displays as well as the participation of the research community in assembling and curating comparative map data.

Databases, Factual↗