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Open Access Research article

nGASP – the nematode genome annotation assessment project

Avril Coghlan1, Tristan J Fiedler2, Sheldon J McKay3, Paul Flicek4, Todd W Harris3, Darin Blasiar5, the nGASP Consortium and Lincoln D Stein3*

  • * Corresponding author: Lincoln D Stein lstein@cshl.edu

  • † Equal contributors

Author Affiliations

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

2 Department of Biological Sciences, Florida Institute of Technology, Melbourne, FL 32901, USA

3 Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA

4 European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK

5 Washington University School of Medicine, St Louis, MO 63108, USA

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BMC Bioinformatics 2008, 9:549  doi:10.1186/1471-2105-9-549

Published: 19 December 2008

Abstract

Background

While the C. elegans genome is extensively annotated, relatively little information is available for other Caenorhabditis species. The nematode genome annotation assessment project (nGASP) was launched to objectively assess the accuracy of protein-coding gene prediction software in C. elegans, and to apply this knowledge to the annotation of the genomes of four additional Caenorhabditis species and other nematodes. Seventeen groups worldwide participated in nGASP, and submitted 47 prediction sets across 10 Mb of the C. elegans genome. Predictions were compared to reference gene sets consisting of confirmed or manually curated gene models from WormBase.

Results

The most accurate gene-finders were 'combiner' algorithms, which made use of transcript- and protein-alignments and multi-genome alignments, as well as gene predictions from other gene-finders. Gene-finders that used alignments of ESTs, mRNAs and proteins came in second. There was a tie for third place between gene-finders that used multi-genome alignments and ab initio gene-finders. The median gene level sensitivity of combiners was 78% and their specificity was 42%, which is nearly the same accuracy reported for combiners in the human genome. C. elegans genes with exons of unusual hexamer content, as well as those with unusually many exons, short exons, long introns, a weak translation start signal, weak splice sites, or poorly conserved orthologs posed the greatest difficulty for gene-finders.

Conclusion

This experiment establishes a baseline of gene prediction accuracy in Caenorhabditis genomes, and has guided the choice of gene-finders for the annotation of newly sequenced genomes of Caenorhabditis and other nematode species. We have created new gene sets for C. briggsae, C. remanei, C. brenneri, C. japonica, and Brugia malayi using some of the best-performing gene-finders.