Much of the data within Model Organism Databases (MODs) comes from manual curation of the primary research literature. Given limited funding and an increasing density of published material, a significant challenge facing all MODs is how to efficiently and effectively prioritize the most relevant research papers for detailed curation. Here, we report recent improvements to the triaging process used by FlyBase. We describe an automated method to directly e-mail corresponding authors of new papers, requesting that they list the genes studied and indicate (‘flag’) the types of data described in the paper using an online tool. Based on the author-assigned flags, papers are then prioritized for detailed curation and channelled to appropriate curator teams for full data extraction. The overall response rate has been 44% and the flagging of data types by authors is sufficiently accurate for effective prioritization of papers. In summary, we have established a sustainable community curation program, with the result that FlyBase curators now spend less time triaging and can devote more effort to the specialized task of detailed data extraction.

Database URL: http://flybase.org/

A combined bioinformatic and genetic approach was used to conduct a systematic analysis of the relationship between ribosomal protein genes and Minute loci in Drosophila melanogaster, allowing the identification of 64 Minute loci corresponding to ribosomal genes.

Background

Mutations in genes encoding ribosomal proteins (RPs) have been shown to cause an array of cellular and developmental defects in a variety of organisms. In Drosophila melanogaster, disruption of RP genes can result in the 'Minute' syndrome of dominant, haploinsufficient phenotypes, which include prolonged development, short and thin bristles, and poor fertility and viability. While more than 50 Minute loci have been defined genetically, only 15 have so far been characterized molecularly and shown to correspond to RP genes.

Results

We combined bioinformatic and genetic approaches to conduct a systematic analysis of the relationship between RP genes and Minute loci. First, we identified 88 genes encoding 79 different cytoplasmic RPs (CRPs) and 75 genes encoding distinct mitochondrial RPs (MRPs). Interestingly, nine CRP genes are present as duplicates and, while all appear to be functional, one member of each gene pair has relatively limited expression. Next, we defined 65 discrete Minute loci by genetic criteria. Of these, 64 correspond to, or very likely correspond to, CRP genes; the single non-CRP-encoding Minute gene encodes a translation initiation factor subunit. Significantly, MRP genes and more than 20 CRP genes do not correspond to Minute loci.

Conclusion

This work answers a longstanding question about the molecular nature of Minute loci and suggests that Minute phenotypes arise from suboptimal protein synthesis resulting from reduced levels of cytoribosomes. Furthermore, by identifying the majority of haplolethal and haplosterile loci at the molecular level, our data will directly benefit efforts to attain complete deletion coverage of the D. melanogaster genome.

The recent completion of the Drosophila melanogaster genomic sequence to high quality, and the availability of a greatly expanded set of Drosophila cDNA sequences, afforded FlyBase the opportunity to significantly improve genomic annotations.

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.