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Gene finding in the chicken genome.

Authors
Journal
BMC Bioinformatics
1471-2105
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Volume
6
Issue
1
Identifiers
DOI: 10.1186/1471-2105-6-131
Keywords
  • Animals
  • Chickens
  • Chromosome Mapping
  • Computational Biology/Methods
  • Dna Primers
  • Dna
  • Complementary/Metabolism
  • Data Interpretation
  • Statistical
  • Databases
  • Genetic
  • Exons
  • Expressed Sequence Tags
  • Gene Expression Profiling
  • Genome
  • Introns
  • Models
  • Statistical
  • Reverse Transcriptase Polymerase Chain Reaction
  • Sequence Alignment
  • Sequence Analysis
  • Dna
  • Software
  • Tissue Distribution
Disciplines
  • Computer Science

Abstract

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

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Gene finding in the chicken genome

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