Background: Despite the continuous production of genome sequence for a number of organisms,/nreliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly/ntrue for genomes for which there is not a large collection of known gene sequences, such as the/nrecently published chicken genome. We used the chicken sequence to test comparative and/nhomology-based gene-finding methods followed by experimental validation as an effective genome/nannotation method./nResults: ...
Background: Despite the continuous production of genome sequence for a number of organisms,/nreliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly/ntrue for genomes for which there is not a large collection of known gene sequences, such as the/nrecently published chicken genome. We used the chicken sequence to test comparative and/nhomology-based gene-finding methods followed by experimental validation as an effective genome/nannotation method./nResults: We performed experimental evaluation by RT-PCR of three different computational gene/nfinders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was/ncomputed and each component of it was evaluated. The results showed that de novo comparative/nmethods can identify up to about 700 chicken genes with no previous evidence of expression, and/ncan correctly extend about 40% of homology-based predictions at the 5' end./nConclusions: De novo comparative gene prediction followed by experimental verification is/neffective at enhancing the annotation of the newly sequenced genomes provided by standard/nhomology-based methods.
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