FlyBase 101 – the basics of navigating FlyBase

FlyBase (http://flybase.org) is the leading database and web portal for genetic and genomic information on the fruit fly Drosophila melanogaster and related fly species. Whether you use the fruit fly as an experimental system or want to apply Drosophila biological knowledge to another field of study, FlyBase can help you successfully navigate the wealth of available Drosophila data. Here, we review the FlyBase web site with novice and less-experienced users of FlyBase in mind and point out recent developments stemming from the availability of genome-wide data from the modENCODE project. The first section of this paper explains the organization of the web site and describes the report pages available on FlyBase, focusing on the most popular, the Gene Report. The next section introduces some of the search tools available on FlyBase, in particular, our heavily used and recently redesigned search tool QuickSearch, found on the FlyBase homepage. The final section concerns genomic data, including recent modENCODE (http://www.modencode.org) data, available through our Genome Browser, GBrowse

FlyBase: enhancing Drosophila Gene Ontology annotations

FlyBase (http://flybase.org) is a database of Drosophila genetic and genomic information. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. This article describes recent changes to the FlyBase GO annotation strategy that are improving the quality of the GO annotation data. Many of these changes stem from our participation in the GO Reference Genome Annotation Project—a multi-database collaboration producing comprehensive GO annotation sets for 12 diverse species

An open and transparent process to select ELIXIR Node Services as implemented by ELIXIR-UK

ELIXIR is the European infrastructure established specifically for the sharing and sustainability of life science data. To provide up-to-date resources and services, ELIXIR needs to undergo a continuous process of refreshing the services provided by its national Nodes. Here we present the approach taken by ELIXIR-UK to address the advice by the ELIXIR Scientific Advisory Board that Nodes need to develop “mechanisms to ensure that each Node continues to be representative of the Bioinformatics efforts within the country”. ELIXIR-UK put in place an open and transparent process to identify potential ELIXIR resources within the UK during late 2015 and early to mid-2016. Areas of strategic strength were identified and Expressions of Interest in these priority areas were requested from the UK community. A set of criteria were established, in discussion with the ELIXIR Hub, and prospective ELIXIR-UK resources were assessed by an independent committee set up by the Node for this purpose. Of 19 resources considered, 14 were judged to be immediately ready to be included in the UK ELIXIR Node’s portfolio. A further five were placed on the Node’s roadmap for future consideration for inclusion. ELIXIR-UK expects to repeat this process regularly to ensure its portfolio continues to reflect its community’s strengths

A FAIR guide for data providers to maximise sharing of human genomic data

It is generally acknowledged that, for reproducibility and progress of human genomic research, data sharing is critical. For every sharing transaction, a successful data exchange is produced between a data consumer and a data provider. Providers of human genomic data (e.g., publicly or privately funded repositories and data archives) fulfil their social contract with data donors when their shareable data conforms to FAIR (findable, accessible, interoperable, reusable) principles. Based on our experiences via Repositive (https://repositive.io), a leading discovery platform cataloguing all shared human genomic datasets, we propose guidelines for data providers wishing to maximise their shared data’s FAIRness. Citation: Corpas M, Kovalevskaya NV, McMurray A, Niel

Expansion of the Gene Ontology knowledgebase and resources

The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/.National Institutes of Health/National Human Genome Research Institute [HG002273] awarded to the PI group formed by (alphabetically) Judith A. Blake, J. Michael Cherry, Suzanna E. Lewis, Paul W. Sternberg and Paul D. Thomas, as well as additional funding awarded to each participating institution. For more details please visit: http://geneontology.org/page/go-consortium-contributors-list. Funding for open access charge: National Institutes of Health/National Human Genome Research Institute [HG002273]

Genome-wide fine-scale recombination rate variation in Drosophila melanogaster

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 diversity

The Australasian COVID-19 Trial (ASCOT) to assess clinical outcomes in hospitalised patients with SARS-CoV-2 infection (COVID-19) treated with lopinavir/ritonavir and/or hydroxychloroquine compared to standard of care: A structured summary of a study protocol for a randomised controlled trial

Objectives: To determine if lopinavir/ritonavir +/- hydroxychloroquine will reduce the proportion of participants who survive without requiring ventilatory support, 15 days after enrolment, in adult participants with non-critically ill SARS-CoV-2 infection. Trial design: ASCOT is an investigator-initiated, multi-centre, open-label, randomised controlled trial. Participants will have been hospitalised with confirmed COVID-19, and will be randomised 1:1:1:1 to receive lopinavir /ritonavir, hydroxychloroquine, both or neither drug in addition to standard of care management. Participants: Participants will be recruited from >80 hospitals across Australia and New Zealand, representing metropolitan and regional centres in both public and private sectors. Admitted patients will be eligible if aged ≥ 18 years, have confirmed SARS-CoV-2 by nucleic acid testing in the past 12 days and are expected to remain an inpatient for at least 48 hours from the time of randomisation. Potentially eligible participants will be excluded if admitted to intensive care or requiring high level respiratory support, are currently receiving study drugs or their use is contraindicated due to allergy, drug interaction or comorbidities (including baseline QTc prolongation of 470ms for women or 480ms for men), or death is anticipated imminently

A Nutrient-Driven tRNA Modification Alters Translational Fidelity and Genome-wide Protein Coding across an Animal Genus

<div><p>Natural selection favors efficient expression of encoded proteins, but the causes, mechanisms, and fitness consequences of evolved coding changes remain an area of aggressive inquiry. We report a large-scale reversal in the relative translational accuracy of codons across 12 fly species in the <i>Drosophila</i>/<i>Sophophora</i> genus. Because the reversal involves pairs of codons that are read by the same genomically encoded tRNAs, we hypothesize, and show by direct measurement, that a tRNA anticodon modification from guanosine to queuosine has coevolved with these genomic changes. Queuosine modification is present in most organisms but its function remains unclear. Modification levels vary across developmental stages in <i>D. melanogaster</i>, and, consistent with a causal effect, genes maximally expressed at each stage display selection for codons that are most accurate given stage-specific queuosine modification levels. In a kinetic model, the known increased affinity of queuosine-modified tRNA for ribosomes increases the accuracy of cognate codons while reducing the accuracy of near-cognate codons. Levels of queuosine modification in <i>D. melanogaster</i> reflect bioavailability of the precursor queuine, which eukaryotes scavenge from the tRNAs of bacteria and absorb in the gut. These results reveal a strikingly direct mechanism by which recoding of entire genomes results from changes in utilization of a nutrient.</p></div