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Gene prediction and verification in a compact genome with numerous small introns.
Tenney, Aaron E; Brown, Randall H; Vaske, Charles; Lodge, Jennifer K; Doering, Tamara L; Brent, Michael R.
Afiliação
  • Tenney AE; Laboratory for Computational Genomics and Department of Computer Science, Washington University, St. Louis, Missouri 63130, USA.
Genome Res ; 14(11): 2330-5, 2004 Nov.
Article em En | MEDLINE | ID: mdl-15479946
ABSTRACT
The genomes of clusters of related eukaryotes are now being sequenced at an increasing rate, creating a need for accurate, low-cost annotation of exon-intron structures. In this paper, we demonstrate that reverse transcription-polymerase chain reaction (RT-PCR) and direct sequencing based on predicted gene structures satisfy this need, at least for single-celled eukaryotes. The TWINSCAN gene prediction algorithm was adapted for the fungal pathogen Cryptococcus neoformans by using a precise model of intron lengths in combination with ungapped alignments between the genome sequences of the two closely related Cryptococcus varieties. This approach resulted in approximately 60% of known genes being predicted exactly right at every coding base and splice site. When previously unannotated TWINSCAN predictions were tested by RT-PCR and direct sequencing, 75% of targets spanning two predicted introns were amplified and produced high-quality sequence. When targets spanning the complete predicted open reading frame were tested, 72% of them amplified and produced high-quality sequence. We conclude that sequencing a small number of expressed sequence tags (ESTs) to provide training data, running TWINSCAN on an entire genome, and then performing RT-PCR and direct sequencing on all of its predictions would be a cost-effective method for obtaining an experimentally verified genome annotation.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Íntrons / Genoma Fúngico / Análise de Sequência de DNA / Cryptococcus neoformans Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2004 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Software / Íntrons / Genoma Fúngico / Análise de Sequência de DNA / Cryptococcus neoformans Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2004 Tipo de documento: Article