62 research outputs found

    The aminoacyl-tRNA synthetases of Drosophila melanogaster.

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    Aminoacyl-tRNA synthetases (aaRSs) ligate amino acids to their cognate tRNAs, allowing them to decode the triplet code during translation. Through different mechanisms aaRSs also perform several non-canonical functions in transcription, translation, apoptosis, angiogenesis and inflammation. Drosophila has become a preferred system to model human diseases caused by mutations in aaRS genes, to dissect effects of reduced translation or non-canonical activities, and to study aminoacylation and translational fidelity. However, the lack of a systematic annotation of this gene family has hampered such studies. Here, we report the identification of the entire set of aaRS genes in the fly genome and we predict their roles based on experimental evidence and/or orthology. Further, we propose a new, systematic and logical nomenclature for aaRSs. We also review the research conducted on Drosophila aaRSs to date. Together, our work provides the foundation for further research in the fly aaRS field.S.J.M. is supported by the FlyBase NIH/NHGRI grant U41HG000739 (W.M. Gelbart, Harvard University, PI; N.H. Brown, University of Cambridge, coPI). J.L. was supported by Cancer Research Switzerland and a SNF grant to B.S., and by a SNSF Early Postdoc Fellowship.This is the final version of the article. It was first available from Taylor & Francis via http://dx.doi.org/10.1080/19336934.2015.110119

    Identification and bioinformatic analysis of neprilysin and neprilysin-like metalloendopeptidases in Drosophila melanogaster.

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    The neprilysin (M13) family of metalloendopeptidases comprises highly conserved ectoenzymes that cleave and thereby inactivate many physiologically relevant peptides in the extracellular space. Impaired neprilysin activity is associated with numerous human diseases. Here, we present a comprehensive list and classification of M13 family members in Drosophila melanogaster. Seven Neprilysin (Nep) genes encode active peptidases, while 21 Neprilysin-like (Nepl) genes encode proteins predicted to be catalytically inactive. RNAseq data demonstrate that all 28 genes are expressed during development, often in a tissue-specific pattern. Most Nep proteins possess a transmembrane domain, whereas almost all Nepl proteins are predicted to be secreted

    Automatic categorization of diverse experimental information in the bioscience literature

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    Background: Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. Results: We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Conclusions: Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort

    The DNA polymerases of Drosophila melanogaster.

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    DNA synthesis during replication or repair is a fundamental cellular process that is catalyzed by a set of evolutionary conserved polymerases. Despite a large body of research, the DNA polymerases of Drosophila melanogaster have not yet been systematically reviewed, leading to inconsistencies in their nomenclature, shortcomings in their functional (Gene Ontology, GO) annotations and an under-appreciation of the extent of their characterization. Here, we describe the complete set of DNA polymerases in D. melanogaster, applying nomenclature already in widespread use in other species, and improving their functional annotation. A total of 19 genes encode the proteins comprising three replicative polymerases (alpha-primase, delta, epsilon), five translesion/repair polymerases (zeta, eta, iota, Rev1, theta) and the mitochondrial polymerase (gamma). We also provide an overview of the biochemical and genetic characterization of these factors in D. melanogaster. This work, together with the incorporation of the improved nomenclature and GO annotation into key biological databases, including FlyBase and UniProtKB, will greatly facilitate access to information about these important proteins

    The Drosophila phenotype ontology

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    BACKGROUND: Phenotype ontologies are queryable classifications of phenotypes. They provide a widely-used means for annotating phenotypes in a form that is human-readable, programatically accessible and that can be used to group annotations in biologically meaningful ways. Accurate manual annotation requires clear textual definitions for terms. Accurate grouping and fruitful programatic usage require high-quality formal definitions that can be used to automate classification. The Drosophila phenotype ontology (DPO) has been used to annotate over 159,000 phenotypes in FlyBase to date, but until recently lacked textual or formal definitions. RESULTS: We have composed textual definitions for all DPO terms and formal definitions for 77% of them. Formal definitions reference terms from a range of widely-used ontologies including the Phenotype and Trait Ontology (PATO), the Gene Ontology (GO) and the Cell Ontology (CL). We also describe a generally applicable system, devised for the DPO, for recording and reasoning about the timing of death in populations. As a result of the new formalisations, 85% of classifications in the DPO are now inferred rather than asserted, with much of this classification leveraging the structure of the GO. This work has significantly improved the accuracy and completeness of classification and made further development of the DPO more sustainable. CONCLUSIONS: The DPO provides a set of well-defined terms for annotating Drosophila phenotypes and for grouping and querying the resulting annotation sets in biologically meaningful ways. Such queries have already resulted in successful function predictions from phenotype annotation. Moreover, such formalisations make extended queries possible, including cross-species queries via the external ontologies used in formal definitions. The DPO is openly available under an open source license in both OBO and OWL formats. There is good potential for it to be used more broadly by the Drosophila community, which may ultimately result in its extension to cover a broader range of phenotypes

    Exploring FlyBase Data Using QuickSearch.

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    FlyBase (flybase.org) is the primary online database of genetic, genomic, and functional information about Drosophila species, with a major focus on the model organism Drosophila melanogaster. The long and rich history of Drosophila research, combined with recent surges in genomic-scale and high-throughput technologies, mean that FlyBase now houses a huge quantity of data. Researchers need to be able to rapidly and intuitively query these data, and the QuickSearch tool has been designed to meet these needs. This tool is conveniently located on the FlyBase homepage and is organized into a series of simple tabbed interfaces that cover the major data and annotation classes within the database. This unit describes the functionality of all aspects of the QuickSearch tool. With this knowledge, FlyBase users will be equipped to take full advantage of all QuickSearch features and thereby gain improved access to data relevant to their research. © 2016 by John Wiley & Sons, Inc
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