Gene Model Annotations for Drosophila melanogaster: Impact of High-Throughput Data
dos Santos, Gilberto
St. Pierre, Susan E.
Gramates, L. Sian
Russo, Susan M.
Gelbart, William M.Note: Order does not necessarily reflect citation order of authors.
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CitationMatthews, B. B., G. dos Santos, M. A. Crosby, D. B. Emmert, S. E. St. Pierre, L. S. Gramates, P. Zhou, et al. 2015. “Gene Model Annotations for Drosophila melanogaster: Impact of High-Throughput Data.” G3: Genes|Genomes|Genetics 5 (8): 1721-1736. doi:10.1534/g3.115.018929. http://dx.doi.org/10.1534/g3.115.018929.
AbstractWe report the current status of the FlyBase annotated gene set for Drosophila melanogaster and highlight improvements based on high-throughput data. The FlyBase annotated gene set consists entirely of manually annotated gene models, with the exception of some classes of small non-coding RNAs. All gene models have been reviewed using evidence from high-throughput datasets, primarily from the modENCODE project. These datasets include RNA-Seq coverage data, RNA-Seq junction data, transcription start site profiles, and translation stop-codon read-through predictions. New annotation guidelines were developed to take into account the use of the high-throughput data. We describe how this flood of new data was incorporated into thousands of new and revised annotations. FlyBase has adopted a philosophy of excluding low-confidence and low-frequency data from gene model annotations; we also do not attempt to represent all possible permutations for complex and modularly organized genes. This has allowed us to produce a high-confidence, manageable gene annotation dataset that is available at FlyBase (http://flybase.org). Interesting aspects of new annotations include new genes (coding, non-coding, and antisense), many genes with alternative transcripts with very long 3′ UTRs (up to 15–18 kb), and a stunning mismatch in the number of male-specific genes (approximately 13% of all annotated gene models) vs. female-specific genes (less than 1%). The number of identified pseudogenes and mutations in the sequenced strain also increased significantly. We discuss remaining challenges, for instance, identification of functional small polypeptides and detection of alternative translation starts.
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