MOTIVATION: The vast majority of introns in protein-coding genes of higher 
eukaryotes have a GT dinucleotide at their 5'-terminus and an AG dinucleotide at 
their 3' end. About 1-2% of introns are non-canonical, with the most abundant 
subtype of non-canonical introns being characterized by GC and AG dinucleotides 
at their 5'- and 3'-termini, respectively. Most current gene prediction 
software, whether based on ab initio or spliced alignment approaches, does not 
include explicit models for non-canonical introns or may exclude their 
prediction altogether. With present amounts of genome and transcript data, it is 
now possible to apply statistical methodology to non-canonical splice site 
prediction. We pursued one such approach and describe the training and 
implementation of GC-donor splice site models for Arabidopsis and rice, with the 
goal of exploring whether specific modeling of non-canonical introns can enhance 
gene structure prediction accuracy.
RESULTS: Our results indicate that the incorporation of non-canonical splice 
site models yields dramatic improvements in annotating genes containing GC-AG 
and AT-AC non-canonical introns. Comparison of models shows differences between 
monocot and dicot species, but also suggests GC intron-specific biases 
independent of taxonomic clade. We also present evidence that GC-AG introns 
occur preferentially in genes with atypically high exon counts.
AVAILABILITY: Source code for the updated versions of GeneSeqer and 
SplicePredictor (distributed with the GeneSeqer code) isavailable at 
http://bioinformatics.iastate.edu/bioinformatics2go/gs/download.html. Web 
servers for Arabidopsis, rice and other plant species are accessible at 
http://www.plantgdb.org/PlantGDB-cgi/GeneSeqer/AtGDBgs.cgi, 
http://www.plantgdb.org/PlantGDB-cgi/GeneSeqer/OsGDBgs.cgi and 
http://www.plantgdb.org/PlantGDB-cgi/GeneSeqer/PlantGDBgs.cgi, respectively. A 
SplicePredictor web server is available at 
http://bioinformatics.iastate.edu/cgi-bin/sp.cgi. Software to generate training 
data and parameterizations for Bayesian splice site models is available at 
http://gremlin1.gdcb.iastate.edu/~volker/SB05B/BSSM4GSQ/