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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 ( 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.

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.

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.