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Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

MotivationLife science research in academia, industry, agriculture, and the health sector depends critically on free and open data resources. ELIXIR (www.elixir-europe.org), the European Research Infrastructure for life sciences data, has identified a set of Core Data Resources within Europe that are of most fundamental importance for the long-term preservation of biological data. We explore characteristics of their usage, impact and assured funding horizon to assess their value and importance as an infrastructure, to understand sustainability of the infrastructure, and to demonstrate a model for assessing Core Data Resources worldwide.ResultsThe nineteen resources currently designated ELIXIR Core Data Resources form a data infrastructure in Europe which is a subset of the worldwide open life science data infrastructure. We show that, from 2014 to 2018, data managed by the Core Data Resources more than tripled while staff numbers increased by less than a tenth. Additionally, support for the Core Data Resources is precarious: together they have assured funding for less than a third of current staff after four years.Our findings demonstrate the importance of the ELIXIR Core Data Resources as repositories for research data and knowledge, while also demonstrating the uncertain nature of the funding environment for this infrastructure. ELIXIR is working towards longer-term support for the Core Data Resources and, through the Global Biodata Coalition, aims to ensure support for the worldwide life science data resource infrastructure of which the ELIXIR Core Data Resources are a subset.Contactrachel.drysdale@elixir-europe.orgSupplementary informationSupplementary data are available at Bioinformatics online.

The Table 1 (EU declaration signatory and membership status) of the original article published online contained several errors: the IARC was incorrectly listed in the table, which only includes countries, and footnote; Croatia, Lithuania, Poland and Portugal were not listed as full EMBL members; Estonia is now listed as a Prospect Member of EMBL; Hungary, Ireland and Israel were incorrectly listed as BBMRI-ERIC members; Iceland was omitted from the table. Hyphens stand for ‘not applicable’; the table and footnote have been corrected accordingly. These errors have now been corrected online and in print.

In order to keep subscribers up-to-date with the latest developments in their field, this current awareness service is provided by John WileySons and contains newly-published material on comparative and functional genomics. Each bibliography is divided into 16 sections. 1 Reviewssymposia; 2 General; 3 Large-scale sequencing and mapping; 4 Genome evolution; 5 Comparative genomics; 6 Gene families and regulons; 7 Pharmacogenomics; 8 Large-scale mutagenesis programmes; 9 Functional complementation; 10 Transcriptomics; 11 Proteomics; 12 Protein structural genomics; 13 Metabolomics; 14 Genomic approaches to development; 15 Technological advances; 16 Bioinformatics. Within each section, articles are listed in alphabetical order with respect to author. If, in the preceding period, no publications are located relevant to any one of these headings, that section will be omitted

FlyBase is a database of genetic and molecular data concerning Drosophila. FlyBase is maintained as a relational database (in Sybase) and is made available as html documents and flat files. The scope of FlyBase includes: genes, alleles (and phenotypes), aberrations, transposons, pointers to sequence data, clones, stock lists, Drosophila workers and bibliographic references. The Encyclopedia of Drosophila is a joint effort between FlyBase and the Berkeley Drosophila Genome Project which integrates FlyBase data with those from the BDGP.

Genes encoding proteins involved in the function of the nervous system can be identified via mutations causing behavioral abnormalities. An example is ether a go-go (eag) in Drosophila melanogaster, which was identified originally as an X-linked mutation that displayed ether-induced leg-shaking behavior. Electrophysiological and genetic evidence suggests that the product of the eag locus is intimately involved in the normal functioning of one or more types of voltage-gated potassium channels. To initiate a molecular analysis of eag we first generated a collection of deletions to pinpoint its cytological location. On the basis of this location, we identified an existing inversion, In(1)sc(29), with one breakpoint at the eag locus and the other in the scute (sc) complex. A genomic library was prepared from In(1)sc(29) and screened with a genomic DNA fragment that spanned the sc breakpoint to isolate DNA from the eag region. Beginning from this starting point over 85 kb of DNA were isolated by chromosome walking. Three additional eag alleles, including two dysgenesis-induced insertion mutations and a γ-ray-induced insertional translocation, were located on the molecular map of the eag locus by Southern blot analysis. The molecular defects associated with these alleles encompass a total of 27 kb within the chromosome walk. A 10-kb transcript derived from this region, which is expressed most abundantly in heads, was identified on Northern blots. Two different eag mutations separated by over 20 kb interrupt the same transcript identifying it as the likely eag message. cDNAs representing a portion of this transcript have been isolated. The genomic DNA sequences from which these cDNAs are derived extend over 37.5 kb, providing a minimum estimate of the size of the eag transcription unit. Ultimately, sequence analysis of these cDNAs should enable us to the identify the eag polypeptide and to elucidate its role in membrane excitability.

FlyBase ( http://flybase.org ) is the primary database of integrated genetic and genomic data about the Drosophilidae, of which Drosophila melanogaster is the most extensively studied species. Information in FlyBase originates from a variety of sources ranging from large-scale genome projects to the primary research literature. Data-types include sequence-level gene models, molecular classification of gene product functions, mutant phenotypes, mutant lesions and chromosome aberrations, gene expression patterns, transgene insertions, and anatomical images. Query tools allow interrogation of FlyBase through DNA or protein sequence, by gene or mutant name, or through terms from the several ontologies used to capture functional, phenotypic, and anatomical data. Links between FlyBase and external databases provide extensive opportunity for extending exploration into other model organism databases and resources of biological and molecular information. This review will introduce the FlyBase web server and query tools.

Background Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear. Results PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowser's navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article. Conclusion We show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully.

FlyBase ( http://flybase.org ) is the primary database of integrated genetic and genomic data about the Drosophilidae, of which Drosophila melanogaster is the most extensively studied species. Information in FlyBase originates from a variety of sources ranging from large-scale genome projects to the primary research literature. Data-types include sequence-level gene models, molecular classification of gene product functions, mutant phenotypes, mutant lesions and chromosome aberrations, gene expression patterns, transgene insertions, and anatomical images. Query tools allow interrogation of FlyBase through DNA or protein sequence, by gene or mutant name, or through terms from the several ontologies used to capture functional, phenotypic, and anatomical data. Links between FlyBase and external databases provide extensive opportunity for extending exploration into other model organism databases and resources of biological and molecular information. This review will introduce the FlyBase web server and query tools.

The sequence and genome annotations of Drosophila melanogaster were initially published in late 1999 and early 2000. Since then, the Berkeley Drosophila Genome Project (BDGP) and FlyBase have improved the quality of the sequence and reviewed the annotations by hand, respectively, to produce an account of the fruit fly genome that is of the highest quality. This review discusses the main features of this process, both from the point of view of the biology revealed in the end result and in the development of software that has been central to this genome sequencing and annotation project.

Many of the signaling properties of neurons and other electrically excitable cells are determined by a diverse family of potassium channels. A number of genes that encode potassium channel polypeptides have been cloned from various organisms on the basis of their sequence similarity to the Drosophila Shaker (Sh) locus. As an alternative strategy, a molecular analysis of other Drosophila genes that were defined by mutations that perturb potassium channel function was undertaken. Sequence analysis of complementary DNA from the ether à go-go (eag) locus revealed that it encodes a structural component of potassium channels that is related to but is distinct from all identified potassium channel polypeptides.

The FlyBase Drosophila genetics database and the public interfaces of the Berkeley Drosophila Genome Project (BDGP) and European Drosophila Genome Project (EDGP) are in the process of integrating. At present, the data of these projects are available from independent, but hyperlinked, WWW sites (FlyBase URL, http://flybase. bio.indiana.edu/; BDGP URL, http://fruitfly.berkeley.edu/; EDGP URL, http://edgp.ebi.ac.uk/ ). Because of the considerable overlap of data classes between the contributions of the Drosophila genome projects and the Drosophila community, the new and enlarged FlyBase consortium views the implementation of a single integrated Drosophila genomics/genetics server as essential to the scientific community. This integration will occur in a stepwise fashion over the next 1-2 years. In this report, the salient features of the current databases and how to interrogate and navigate the extensive data sets are discussed.

We have used mutations in the newly identified gene myoblast city to investigate the founder cell hypothesis of muscle development in Drosophila melanogaster. In embryos mutant for myoblast city the fusion of myoblasts into multinucleate muscles is virtually abolished. Nevertheless, a subset of the myoblasts develop specific muscle-like characteristics, including gene expression appropriate to particular muscles, migration to the appropriate part of the segment, correct position and orientation, and contact by motor neurons. We suggest that this subset of myoblasts represents the proposed muscle founder cells and we draw an analogy between these founder cells and the muscle pioneers described for grasshopper muscle development.

We have begun a genetic analysis to dissect the process of myogenesis by surveying the X chromosome of Drosophila melanogaster for mutations that affect embryonic muscle development. Using polarised light microscopy and antibody staining techniques we analysed embryos hemizygous for a series of 67 deletion mutations that together cover an estimated 85% of the X chromosome, or 16.5% of the genome. Whereas the mature wild type embryo has a regular array of contractile muscles that insert into the epidermis, 31 of the deletion mutants have defects in muscle pattern, contractility or both, that cannot be attributed simply to epidermal defects and identify functions required for wild type muscle development. We have defined mutant pattern phenotypes that can be described in terms of muscle absences, incomplete myoblast fusion, failure of attachment of the muscle to the epidermis or mispositioning of attachment sites. Thus muscle development can be mutationally disrupted in characteristic and interpretable ways. The areas of overlap of the 31 deletions define 19 regions of the X chromosome that include genes whose products are essential for various aspects of myogenesis. We conclude that our screen can usefully identify loci coding for gene products essential in muscle development.

Background: The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences. Results: Although the number of predicted protein-coding genes in Drosophila remains essentially unchanged, the revised annotation significantly improves gene models, resulting in structural changes to 85% of the transcripts and 45% of the predicted proteins. We annotated transposable elements and non-protein-coding RNAs as new features, and extended the annotation of untranslated (UTR) sequences and alternative transcripts to include more than 70% and 20% of genes, respectively. Finally, cDNA sequence provided evidence for dicistronic transcripts, neighboring genes with overlapping UTRs on the same DNA sequence strand, alternatively spliced genes that encode distinct, non-overlapping peptides, and numerous nested genes. Conclusions: Identification of so many unusual gene models not only suggests that some mechanisms for gene regulation are more prevalent than previously believed, but also underscores the complex challenges of eukaryotic gene prediction. At present, experimental data and human curation remain essential to generate high-quality genome annotations.

The first recorded scientific publication on Drosophila was 310 years ago (Mentzel, 1684). By 1980 about 35,000 papers on Drosophila had been published and at the time of writing this total had risen to over 60,000. By the year 2000, there will be over 80,000 Drosophila publications — and the on-going publication rate will be more than 4,000 a year. There is nothing unique in this rate of growth — it is typical for any “active” subject to double its output every fifteen years (see de Solla Price, 1986). Sooner or later, of course, the curve must plateau but, until it does, the individual scientist faces an obvious problem. Not all of the papers published will be of the standard of those in Development. Nevertheless, just sifting those that are worthy of reading from those that are not will be (indeed is) a daunting task. What is to be done? The answer is obvious, we must exploit the power of computers to point us to papers that we need to read. We must also exploit the power of computers to provide us with basic data about our organism. Luckily, there is every prospect that the power of engines to process and access these data will increase, and their relative cost decrease, with the growth in scientific information.