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Genome Biol ; 5(1): R3, 2003.
Artigo em Inglês | MEDLINE | ID: mdl-14709175

RESUMO

BACKGROUND: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software. RESULTS: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly. CONCLUSIONS: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species.


Assuntos
Drosophila melanogaster/genética , Perfilação da Expressão Gênica/métodos , Genes de Insetos/fisiologia , Genoma , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Animais , Análise por Conglomerados , Biologia Computacional/métodos , Biologia Computacional/estatística & dados numéricos , Perfilação da Expressão Gênica/estatística & dados numéricos , Hibridização In Situ/métodos , Modelos Genéticos , Dados de Sequência Molecular , Análise de Sequência com Séries de Oligonucleotídeos/estatística & dados numéricos , Valor Preditivo dos Testes , Pseudogenes/genética , Interferência de RNA/fisiologia , Reação em Cadeia da Polimerase Via Transcriptase Reversa/métodos
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