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A computational and experimental approach to validating annotations and gene predictions in the Drosophila melanogaster genome.


ABSTRACT: Five years after the completion of the sequence of the Drosophila melanogaster genome, the number of protein-coding genes it contains remains a matter of debate; the number of computational gene predictions greatly exceeds the number of validated gene annotations. We have assembled a collection of >10,000 gene predictions that do not overlap existing gene annotations and have developed a process for their validation that allows us to efficiently prioritize and experimentally validate predictions from various sources by sequencing RT-PCR products to confirm gene structures. Our data provide experimental evidence for 122 protein-coding genes. Our analyses suggest that the entire collection of predictions contains only approximately 700 additional protein-coding genes. Although we cannot rule out the discovery of genes with unusual features that make them refractory to existing methods, our results suggest that the D. melanogaster genome contains approximately 14,000 protein-coding genes.

SUBMITTER: Yandell M 

PROVIDER: S-EPMC545494 | biostudies-literature | 2005 Feb

REPOSITORIES: biostudies-literature

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A computational and experimental approach to validating annotations and gene predictions in the Drosophila melanogaster genome.

Yandell Mark M   Bailey Adina M AM   Misra Sima S   Shu ShengQiang S   Wiel Colin C   Evans-Holm Martha M   Celniker Susan E SE   Rubin Gerald M GM  

Proceedings of the National Academy of Sciences of the United States of America 20050124 5


Five years after the completion of the sequence of the Drosophila melanogaster genome, the number of protein-coding genes it contains remains a matter of debate; the number of computational gene predictions greatly exceeds the number of validated gene annotations. We have assembled a collection of >10,000 gene predictions that do not overlap existing gene annotations and have developed a process for their validation that allows us to efficiently prioritize and experimentally validate predictions  ...[more]

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