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The translation factors of Drosophila melanogaster

Steven J. Marygold, Helen Attrill, Paul Lasko
2016 Fly  
Synthesis of polypeptides from mRNA (translation) is a fundamental cellular process that is coordinated and catalyzed by a set of canonical 'translation factors'. Surprisingly, the translation factors of Drosophila melanogaster have not yet been systematically identified, leading to inconsistencies in their nomenclature and shortcomings in functional (Gene Ontology, GO) annotations. Here, we describe the complete set of translation factors in D. melanogaster, applying nomenclature already in
more » ... espread use in other species, and revising their functional annotation. The collection comprises 43 initiation factors, 12 elongation factors, 3 release factors and 6 recycling factors, totaling 64 of which 55 are cytoplasmic and 9 are mitochondrial. We also provide an overview of notable findings and particular insights derived from Drosophila about these factors. This catalog, together with the incorporation of the improved nomenclature and GO annotation into FlyBase, will greatly facilitate access to information about the functional roles of these important proteins.
doi:10.1080/19336934.2016.1220464 pmid:27494710 pmcid:PMC5354226 fatcat:jfgfmusbjfc67ch7jx3j5ho5oi

Growth Signaling: TSC Takes Its Place

Steven J Marygold, Sally J Leevers
2002 Current Biology  
The protein products of the tumor suppressor genes tuberous sclerosis complex 1 and 2 form a protein complex, TSC1-TSC2, that inhibits growth. Several new studies suggest that TSC1-TSC2 does this by inhibiting TOR and S6 kinase, and that PI 3kinase-Akt signaling relieves this inhibition. How growth and cell size are controlled is poorly understood, but receiving increasing attention from researchers. What has become clear in recent years is that two signal transduction pathways are major
more » ... ors of growth (mass increase) and cell size in organisms as diverse as insects and mammals. One of these is the pathway involving phosphatidylinositol 3kinase (PI 3-kinase) and the protein kinase Akt; the second is the pathway that responds to nutrient supply and involves the 'target of rapamycin' (TOR) protein (reviewed in [1,2]). Although these pathways are thought to converge at some level, the mechanisms through which this occurs have so far been elusive. Earlier work in the fruit fly Drosophila showed that dTsc1 and dTsc2, homologs of the human tumor suppressor gene products TSC1 (also known as hamartin) and TSC2 (also called tuberin), function as a complex in vivo that restricts cell proliferation and reduces cell size [3-6]. Interestingly, genetic epistasis analyses suggested that dTsc1-dTsc2 acts downstream of dAkt and upstream of the dTOR target, dS6 kinase [4-6]. A flurry of recent research [7-14] has now confirmed these ideas, placing TSC1-TSC2 right at the center of the growth signaling network. Collectively, these new papers show that TSC1-TSC2 inhibits S6 kinase by repressing TOR activity, and that TSC1-TSC2 is phosphorylated and inactivated by Akt. (Figure 1) [1,2] . In brief, insulin, or an insulin-like ligand, binds to and activates its cognate receptor, resulting in activation of PI 3-kinase and consequent production of 3phosphoinositides. This process is antagonized by the lipid phosphatase encoded by the tumor suppressor gene PTEN. The increased 3-phosphoinositide level leads to the phosphorylation and activation of the serine/threonine kinase Akt. Studies in both mammalian cells and Drosophila established the existence of a signaling network that links insulin stimulation and nutrient availability to the up-regulation of translation and cell growth The activation of PI 3-kinase-Akt signaling can have numerous downstream effects [2]. One appears to be the activation of S6 kinase as, for example, phosphorylation of a key residue in the carboxyl terminus of the protein -threonine 389 in human S6 kinase 1 -is Dispatch
doi:10.1016/s0960-9822(02)01294-0 pmid:12445406 fatcat:k2njlh6cuzed3eb7sr6snliwrm

Using FlyBase to Find Functionally Related Drosophila Genes [chapter]

Alix J. Rey, Helen Attrill, Steven J. Marygold
2018 Msphere  
For more than 25 years, FlyBase (flybase.org) has served as an online database of biological information on the genus Drosophila, concentrating on the model organism D. melanogaster. Traditionally, FlyBase data have been organized and presented at a gene-by-gene level, which remains a useful perspective when the object of interest is a specific gene or gene product. However, in the modern era of a fully sequenced genome and an increasingly characterized proteome, it is often desirable to
more » ... and analyze lists of genes related by a common function. This may be achieved in FlyBase by searching for genes annotated with relevant Gene Ontology (GO) terms and/or protein domain data. In addition, FlyBase provides preassembled lists of functionally related D. melanogaster genes within "Gene Group" reports. These are compiled manually from the published literature or expert databases and greatly facilitate access to, and analysis of, established gene sets. This chapter describes protocols to produce lists of functionally related genes in FlyBase using GO annotations, protein domain data and the Gene Groups resource, and provides guidance and advice for their further analysis and processing.
doi:10.1007/978-1-4939-7737-6_16 pmid:29761468 pmcid:PMC5996772 fatcat:4s77pj47u5gbfmo57eaa6jefl4

Using FlyBase, a Database of Drosophila Genes and Genomes [chapter]

Steven J. Marygold, Madeline A. Crosby, Joshua L. Goodman
2016 Msphere  
Marygold et al. Page 26 Methods Mol Biol. Author manuscript; available in PMC 2017 January 01. et al. Page 28 Marygold et al.  ...  Marygold Table 3 Precomputed bulk data files available from FlyBase.  ... 
doi:10.1007/978-1-4939-6371-3_1 pmid:27730573 pmcid:PMC5107610 fatcat:gbtsjk6xj5esbp6wt6ttdswhp4

The aminoacyl-tRNA synthetases of Drosophila melanogaster

Jiongming Lu, Steven J Marygold, Walid H Gharib, Beat Suter
2015 Fly  
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
more » ... lational 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.
doi:10.1080/19336934.2015.1101196 pmid:26761199 pmcid:PMC4826098 fatcat:n2iafrdqofbq7mwewpc6tpsgye

In silico identification of Drosophila melanogaster genes encoding RNA polymerase subunits [article]

Steven J Marygold, Nazif Alic, David S Gilmour, Savraj S Grewal
2020 microPublication Biology  
Citation: Marygold, SJ; Alic, N; Gilmour, DS; Grewal, SS (2020).  ... 
doi:10.17912/micropub.biology.000320 pmid:33274328 pmcid:PMC7704258 fatcat:bsovu3yt6jghthztvumnchdhcu

Editorial: Invertebrate UDP-Glycosyltransferases: Nomenclature, Diversity and Functions

Seung-Joon Ahn, Thomas Chertemps, Martine Maïbèche, Steven J. Marygold, Thomas Van Leeuwen
2021 Frontiers in Physiology  
Ahn and Marygold present a comprehensive example of UGT nomenclature practice in the fruit fly, Drosophila melanogaster, though it can be used as a standard reference for Diptera (flies and mosquitoes)  ... 
doi:10.3389/fphys.2021.748290 pmid:34552512 pmcid:PMC8450408 fatcat:j3l6kvu4qzhzhjyho73izfvsue

Genetic characterization of ebi reveals its critical role in Drosophila wing growth

Steven J. Marygold, Cherryl Walker, Mariam Orme, Sally Leevers
2011 Fly  
doi:10.4161/fly.5.4.18276 pmid:22041576 pmcid:PMC3266070 fatcat:da3lctn54nc6vm2kwmuogwwoty

The UDP-Glycosyltransferase Family in Drosophila melanogaster: Nomenclature Update, Gene Expression and Phylogenetic Analysis

Seung-Joon Ahn, Steven J. Marygold
2021 Frontiers in Physiology  
Copyright © 2021 Ahn and Marygold. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).  ... 
doi:10.3389/fphys.2021.648481 pmid:33815151 pmcid:PMC8010143 fatcat:dbpskftj45cxlnn3stbnepcyia

The DNA polymerases of Drosophila melanogaster

Steven J. Marygold, Helen Attrill, Elena Speretta, Kate Warner, Michele Magrane, Maria Berloco, Sue Cotterill, Mitch McVey, Yikang Rong, Masamitsu Yamaguchi
2020 Fly  
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
more » ... es 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.
doi:10.1080/19336934.2019.1710076 pmid:31933406 pmcid:PMC7714529 fatcat:zy34nvn4fvelbaqanoumartwse

FlyBase: improvements to the bibliography

Steven J. Marygold, Paul C. Leyland, Ruth L. Seal, Joshua L. Goodman, Jim Thurmond, Victor B. Strelets, Robert J. Wilson
2012 Nucleic Acids Research  
An accurate, comprehensive, non-redundant and up-to-date bibliography is a crucial component of any Model Organism Database (MOD). Principally, the bibliography provides a set of references that are specific to the field served by the MOD. Moreover, it serves as a backbone to which all curated biological data can be attributed. Here, we describe the organization and main features of the bibliography in FlyBase (flybase.org), the MOD for Drosophila melanogaster. We present an overview of the
more » ... ent content of the bibliography, the pipeline for identifying and adding new references, the presentation of data within Reference Reports and effective methods for searching and retrieving bibliographic data. We highlight recent improvements in these areas and describe the advantages of using the FlyBase bibliography over alternative literature resources. Although this article is focused on bibliographic data, many of the features and tools described are applicable to browsing and querying other datasets in FlyBase.
doi:10.1093/nar/gks1024 pmid:23125371 pmcid:PMC3531214 fatcat:hibhwutfvbashm6jsnxgadwpku

The Drosophila phenotype ontology

David Osumi-Sutherland, Steven J Marygold, Gillian H Millburn, Peter A McQuilton, Laura Ponting, Raymund Stefancsik, Kathleen Falls, Nicholas H Brown, Georgios V Gkoutos
2013 Journal of Biomedical Semantics  
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
more » ... y (DPO) has been used to annotate over 159,000 phenotypes in FlyBase to date, but until recently lacked textual or formal definitions. 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. 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.
doi:10.1186/2041-1480-4-30 pmid:24138933 pmcid:PMC3816596 fatcat:tu5xlh2svfh7voqrmxuk7cs3km

FlyBase: establishing a Gene Group resource forDrosophila melanogaster

Helen Attrill, Kathleen Falls, Joshua L. Goodman, Gillian H. Millburn, Giulia Antonazzo, Alix J. Rey, Steven J. Marygold
2015 Nucleic Acids Research  
Many publications describe sets of genes or gene products that share a common biology. For example, genome-wide studies and phylogenetic analyses identify genes related in sequence; high-throughput genetic and molecular screens reveal functionally related gene products; and advanced proteomic methods can determine the subunit composition of multiprotein complexes. It is useful for such gene collections to be presented as discrete lists within the appropriate Model Organism Database (MOD) so
more » ... researchers can readily access these data alongside other relevant information. To this end, FlyBase (flybase.org), the MOD for Drosophila melanogaster, has established a 'Gene Group' resource: high-quality sets of genes derived from the published literature and organized into individual report pages. To facilitate further analyses, Gene Group Reports also include convenient download and analysis options, together with links to equivalent gene groups at other databases. This new resource will enable researchers with diverse backgrounds and interests to easily view and analyse acknowledged D. melanogaster gene sets and compare them with those of other species.
doi:10.1093/nar/gkv1046 pmid:26467478 pmcid:PMC4702782 fatcat:2ljorlbf4jgkrilfxniusk6pcy

Exploring FlyBase Data Using QuickSearch

Steven J. Marygold, Giulia Antonazzo, Helen Attrill, Marta Costa, Madeline A. Crosby, Gilberto dos Santos, Joshua L. Goodman, L. Sian Gramates, Beverley B. Matthews, Alix J. Rey, Jim Thurmond
2016 Current Protocols in Bioinformatics  
Much of these data are partitioned across ~20 'data classes' within FlyBase (Marygold et al., 2016; Table 1 ).  ...  Large Dataset Metadata Simple, Data Class: large dataset metadata Gene Groups Simple, Gene Groups Human Disease Models Simple, Human Disease Marygold et al.  ... 
doi:10.1002/cpbi.19 pmid:27930807 pmcid:PMC5152691 fatcat:gak43qcvjndcphz774srcxvzkq

Publishing Interactive Articles: Integrating Journals And Biological Databases

Karen Yook, Karen Yook, Arun Rangarajan, Hans-Michael Muller, Paul Sternberg, Tracey DePellegrin-Connelly, Tim Schedl, Mike Cherry, William Gelbart, Juancarlos Chan, Stephen Haenel, Lolly Otis (+3 others)
2010 Nature Precedings  
doi:10.1038/npre.2010.5146.1 fatcat:ktgy4cks2nhdjjr6ffqpa74poa
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