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Gene finding in the chicken genome

Eduardo Eyras1*, Alexandre Reymond23, Robert Castelo1, Jacqueline M Bye4, Francisco Camara1, Paul Flicek5, Elizabeth J Huckle4, Genis Parra1, David D Shteynberg5, Carine Wyss2, Jane Rogers4, Stylianos E Antonarakis2, Ewan Birney6, Roderic Guigo1 and Michael R Brent5

Author Affiliations

1 Research Group in Biomedical Informatics, Institut Municipal d'Investigacio Medica/Universitat Pompeu Fabra/Centre de Regulacio Genomica, E08003 Barcelona, Catalonia, Spain

2 Department of Genetic Medicine and Development, University of Geneva, Medical School and University Hospital of Geneva, CMU, 1, rue Michel Servet, 1211 Geneva, Switzerland

3 Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland

4 The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK

5 Laboratory for Computational Genomics and Department of Computer Science, Campus Box 1045, Washington University, One Brookings Drive, St Louis, Missouri 63130, USA

6 EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

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BMC Bioinformatics 2005, 6:131  doi:10.1186/1471-2105-6-131

Published: 30 May 2005



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.


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.


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.