ParameciumDB in 2011: new tools and new data for functional and comparative genomics of the model ciliate Paramecium tetraurelia

ParameciumDB is a community model organism database built with the GMOD toolkit to integrate the genome and biology of the ciliate Paramecium tetraurelia. Over the last four years, post-genomic data from proteome and transcriptome studies has been incorporated along with predicted orthologs in 33 species, annotations from the community and publications from the scientific literature. Available tools include BioMart for complex queries, GBrowse2 for genome browsing, the Apollo genome editor for expert curation of gene models, a Blast server, a motif finder, and a wiki for protocols, nomenclature guidelines and other documentation. In-house tools have been developed for ontology browsing and evaluation of off-target RNAi matches. Now ready for next-generation deep sequencing data and the genomes of other Paramecium species, this open-access resource is available at http://paramecium.cgm.cnrs-gif.fr

SOBA: sequence ontology bioinformatics analysis

The advent of cheaper, faster sequencing technologies has pushed the task of sequence annotation from the exclusive domain of large-scale multi-national sequencing projects to that of research laboratories and small consortia. The bioinformatics burden placed on these laboratories, some with very little programming experience can be daunting. Fortunately, there exist software libraries and pipelines designed with these groups in mind, to ease the transition from an assembled genome to an annotated and accessible genome resource. We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi

Petrological and geochemical characteristics of the mafic–ultramafic Americano do Brasil Complex, central Brazil, and the implications for its genesis

The Americano do Brasil Complex occurs in the Neoproterozoic Goias Magmatic Arc, central Brazil. It is composed of two mafic–ultramafic cumulate sequences, intruded into granodioritic gneisses. Although deformed and partially recrystallized by a regional metamorphic overprint, the complex still preserves relict igneous features, such as adcumulate to heteradcumulate textures. The Northern sequence is mostly composed of olivine and olivine-clinopyroxene cumulates, whereas the Southern consists mainly of two-pyroxene cumulate rocks, with plagioclase and olivine cumulates occurring in lesser amounts. The complex has three main orebodies, with textures that range from disseminated to massive sulfide breccias with durchbewegung texture. Thermodynamic modeling using a single picrite parental magma composition can predict cumulate rock compositions and mineral modes similar to all of the observed cumulate rock compositions of the Americano do Brasil Complex. Equilibrium crystallization of the liquid and assimilation-batch-crystallization involving up to 45 % of the host gneisses in the upper crust produces solids similar to the cumulates described in the Northern and Southern sequences, respectively. Modeled pressure–temperature emplacement conditions of the magma were c.a. 2.5 kbar and 1310 °C. Both sequences have similar incompatible trace element patterns which, together with the results of the modeling, imply a broadly comagmatic origin

Atmospheric conditions and their effect on ball-milled magnesium diboride

Magnesium diboride bulk pellets were fabricated from pre-reacted MgB2 powder ball milled with different amounts of exposure to air. Evidence of increased electron scattering including increased resistivity, depressed Tc, and enhanced Hc2 of the milled and heat treated samples were observed as a result of increased contact with air. These and other data were consistent with alloying with carbon as a result of exposure to air. A less clear trend of decreased connectivity associated with air exposure was also observed. In making the case that exposure to air should be considered a doping process, these results may explain the wide varibability of "undoped" MgB2 properties extant in the literature.Comment: Work presented at ASC 2006 in Seattl

Nanoscale grains, high irreversibility field, and large critical current density as a function of high energy ball milling time in C-doped magnesium diboride

Magnesium diboride (MgB2) powder was mechanically alloyed by high energy ball milling with C to a composition of Mg(B0.95C0.05)2 and then sintered at 1000 C in a hot isostatic press. Milling times varied from 1 minute to 3000 minutes. Full C incorporation required only 30-60 min of milling. Grain size of sintered samples decreased with increased milling time to less than 30 nm for 20-50 hrs of milling. Milling had a weak detrimental effect on connectivity. Strong irreversibility field (H*) increase (from 13.3 T to 17.2 T at 4.2 K) due to increased milling time was observed and correlated linearly with inverse grain size (1/d). As a result, high field Jc benefited greatly from lengthy powder milling. Jc(8 T, 4.2 K) peaked at > 80,000 A/cm2 with 1200 min of milling compared with only ~ 26,000 A/cm2 for 60 min of milling. This non-compositional performance increase is attributed to grain refinement of the unsintered powder by milling, and to the probable suppression of grain growth by milling-induced MgO nano-dispersions.Comment: 12 pages, 11 figure

The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or ‘ontologies’. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium has set in train a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing a process of coordinated reform, and new ontologies being created, on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable, logically well-formed, and to incorporate accurate representations of biological reality. We describe the OBO Foundry initiative, and provide guidelines for those who might wish to become involved in the future

Logical Development of the Cell Ontology

<p>Abstract</p> <p>Background</p> <p>The Cell Ontology (CL) is an ontology for the representation of <it>in vivo </it>cell types. As biological ontologies such as the CL grow in complexity, they become increasingly difficult to use and maintain. By making the information in the ontology computable, we can use automated reasoners to detect errors and assist with classification. Here we report on the generation of computable definitions for the hematopoietic cell types in the CL.</p> <p>Results</p> <p>Computable definitions for over 340 CL classes have been created using a genus-differentia approach. These define cell types according to multiple axes of classification such as the protein complexes found on the surface of a cell type, the biological processes participated in by a cell type, or the phenotypic characteristics associated with a cell type. We employed automated reasoners to verify the ontology and to reveal mistakes in manual curation. The implementation of this process exposed areas in the ontology where new cell type classes were needed to accommodate species-specific expression of cellular markers. Our use of reasoners also inferred new relationships within the CL, and between the CL and the contributing ontologies. This restructured ontology can be used to identify immune cells by flow cytometry, supports sophisticated biological queries involving cells, and helps generate new hypotheses about cell function based on similarities to other cell types.</p> <p>Conclusion</p> <p>Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.</p

Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease.

Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype-phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be overcome if we are going to improve detection rates and help the majority of patients that still remain without a molecular diagnosis after state-of-the-art genomic interpretation

Badger-an accessible genome exploration environment

Summary: High-quality draft genomes are now easy to generate, as sequencing and assembly costs have dropped dramatically. However, building a user-friendly searchable Web site and database for a newly annotated genome is not straightforward. Here we present Badger, a lightweight and easy-to-install genome exploration environment designed for next generation non-model organism genomes. Availability: Badger is released under the GPL and is available at http://badger.bio.ed.ac.uk/. We show two working examples: (i) a test dataset included with the source code, and (ii) a collection of four filarial nematode genomes. Contact: [email protected]