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Nucleic Acids Research, 2003, Vol. 31, No. 20 5877-5885
© 2003 Oxford University Press

An organism-specific method to rank predicted coding regions in Trypanosoma brucei

Shuba Gopal*, George A. M. Cross1 and Terry Gaasterland

Laboratory of Computational Genomics and 1 Laboratory of Molecular Parasitology, The Rockefeller University, 1230 York Avenue, Box 250, New York, NY 10021, USA

*To whom correspondence should be addressed. Tel: +1 585 475 4498; Fax: +1 475 2533; Email: shuba{at}genomes.rockefeller.edu

Genome annotation in differently evolved organisms presents challenges because the lack of sequence-based homology limits the ability to determine the function of putative coding regions. To provide an alternative to annotation by sequence homology, we developed a method that takes advantage of unusual trypanosomatid biology and skews in nucleotide composition between coding regions and upstream regions to rank putative open reading frames based on the likelihood of coding. The method is 93% accurate when tested on known genes. We have applied our method to the full complement of open reading frames on Chromosome I of Trypanosoma brucei, and we can predict with high confidence that 226 putative coding regions are likely to be functional. Methods such as the one described here for discriminating true coding regions are critical for genome annotation when other sources of evidence for function are limited.


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