Logitlinear models for the prediction of splice sites in plant pre-mRNA sequences

Abstract

Pre-mRNA splicing in plants, while generally similar to the processes in vertebrates and yeast, is thought to involve plant specific cis-acting elements. Both mono-cot and dicot introns are typically strongly enriched in U nucleotides, and AU-or U-rich segments are thought to be involved in intron recognition, splice site selection , and splicing efficiency. We have applied logit-linear models to find optimal combinations of splice site variables for the purpose of separating true splice sites from a large excess of potential sites. It is shown that plant splice site prediction from sequence inspection is greatly improved when compositional contrast between exons and introns is considered in addition to degree of matching to the splice site consensus (signal quality). The best model involves subclassifica-tion of splice sites according to the identity of the base immediately upstream of the GU and AG signals and gives substantial performance gains compared with conventional profile methods.