Gene prediction and verification in a compact genome with numerous small introns

AUTOR(ES)

Tenney, Aaron E.

FONTE

Cold Spring Harbor Laboratory Press

RESUMO

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 ∼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.

Documentos Relacionados

• Unexpected abundance of self-splicing introns in the genome of bacteriophage Twort: Introns in multiple genes, a single gene with three introns, and exon skipping by group I ribozymes
• NotI flanking sequences: a tool for gene discovery and verification of the human genome
• Spliced-Leader RNA trans Splicing in a Chordate, Oikopleura dioica, with a Compact Genome†
• Mercury selection of allozymes in marine organisms: Prediction and verification in nature
• Hyperinsulinemia after pancreatic transplantation. Prediction by a novel computer model and in vivo verification.