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1.
Genome Biol ; 5(1): R3, 2003.
Artículo en Inglés | MEDLINE | ID: mdl-14709175

RESUMEN

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.


Asunto(s)
Drosophila melanogaster/genética , Perfilación de la Expresión Génica/métodos , Genes de Insecto/fisiología , Genoma , Análisis de Secuencia por Matrices de Oligonucleótidos/métodos , Animales , Análisis por Conglomerados , Biología Computacional/métodos , Biología Computacional/estadística & datos numéricos , Perfilación de la Expresión Génica/estadística & datos numéricos , Hibridación in Situ/métodos , Modelos Genéticos , Datos de Secuencia Molecular , Análisis de Secuencia por Matrices de Oligonucleótidos/estadística & datos numéricos , Valor Predictivo de las Pruebas , Seudogenes/genética , Interferencia de ARN/fisiología , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa/métodos
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