Annotation of the Drosophila melanogastereuchromatic genome: a systematic review

Sima Misra(University of California, Berkeley), Madeline A. Crosby(Harvard University), Chris Mungall(Howard Hughes Medical Institute), Beverley B Matthews(Harvard University), Kathryn S. Campbell(Harvard University), Pavel Hradecky(Harvard University), Yanmei Huang(Harvard University), Joshua S. Kaminker(University of California, Berkeley), Gillian Millburn(University of Cambridge), Simon Prochnik(University of California, Berkeley), Christopher D. Smith(University of California, Berkeley), Jonathan L. Tupy(University of California, Berkeley), Eleanor J Whitfield(European Bioinformatics Institute), Leyla Bayraktaroglu(Harvard University), Benjamin P. Berman(University of California, Berkeley), Brian R. Bettencourt(Harvard University), S Celniker(Lawrence Berkeley National Laboratory), Aubrey DNJ de Grey(University of Cambridge), Rachel Drysdale(University of Cambridge), Nomi L. Harris(Lawrence Berkeley National Laboratory), J Richter(Howard Hughes Medical Institute), Susan Russo(Harvard University), Andrew J. Schroeder(Harvard University), Shengqiang Shu(University of California, Berkeley), Mark Stapleton(Lawrence Berkeley National Laboratory), C. Yamada(University of Cambridge), Michael Ashburner(University of Cambridge), William M Gelbart(Harvard University), Gerald M. Rubin(Howard Hughes Medical Institute), Suzanna Lewis(University of California, Berkeley)
Genome biology
December 31, 2002
Cited by 384Open Access
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Abstract

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.


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