A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana

Plant SR proteins and their functions

SR proteins are a family of splicing factors important for splice site recognition and spliceosome assembly. Their ability to bind to RNA and to interact with proteins as well identifies them as important players in splice site choice and alternative splicing. Plants possess twice as many SR proteins as animals, and some of the subfamilies are plant specific. Arabidopsis SR proteins are involved in different aspects of plant growth and development as well as in responses to environmental cues. The plant-specific subfamilies have been shown to be regulated by alternative splicing events, which are highly conserved in evolution. The tight regulation of splicing factors by alternative splicing might allow coordinated responses of their target genes.

Accurate splice site prediction using support vector machines

BACKGROUND

For splice site recognition, one has to solve two classification problems: discriminating true from decoy splice sites for both acceptor and donor sites. Gene finding systems typically rely on Markov Chains to solve these tasks.

RESULTS

In this work we consider Support Vector Machines for splice site recognition. We employ the so-called weighted degree kernel which turns out well suited for this task, as we will illustrate in several experiments where we compare its prediction accuracy with that of recently proposed systems. We apply our method to the genome-wide recognition of splice sites in Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Danio rerio, and Homo sapiens. Our performance estimates indicate that splice sites can be recognized very accurately in these genomes and that our method outperforms many other methods including Markov Chains, GeneSplicer and SpliceMachine. We provide genome-wide predictions of splice sites and a stand-alone prediction tool ready to be used for incorporation in a gene finder.

AVAILABILITY

Data, splits, additional information on the model selection, the whole genome predictions, as well as the stand-alone prediction tool are available for download at http://www.fml.mpg.de/raetsch/projects/splice.

Features generated for computational splice-site prediction correspond to functional elements

Background

Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals.

Results

We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods.

Conclusion

Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.

Evidence for a trade-off between translational efficiency and splicing regulation in determining synonymous codon usage in Drosophila melanogaster

In Drosophila melanogaster, synonymous codons corresponding to the most abundant cognate tRNAs are used more frequently, especially in highly expressed genes. Increased use of such "optimal" codons is considered an adaptation for translational efficiency. Need it always be the case that selection should favor the use of a translationally optimal codon? Here, we investigate one possible confounding factor, namely, the need to specify information in exons necessary to enable correct splicing. As expected from such a model, in Drosophila many codons show different usage near intron-exon boundaries versus exon core regions. However, this finding is in principle also consistent with Hill-Robertson effects modulating usage of translationally optimal codons. However, several results support the splice model over the translational selection model: 1) the trends in codon usage are strikingly similar to those in mammals in which codon usage near boundaries correlates with abundance in exonic splice enhancers (ESEs), 2) codons preferred near boundaries tend to be enriched for A and avoid C (conversely those avoided near boundaries prefer C rather than A), as expected were ESEs involved, and 3) codons preferred near boundaries are typically not translationally optimal. We conclude that usage of translationally optimal codons usage is compromised in the vicinity of splice junctions in intron-containing genes, to the effect that we observe higher levels of usage of translationally optimal codons at the center of exons. On the gene level, however, controlling for known correlates of codon bias, the impact on codon usage patterns is quantitatively small. These results have implications for inferring aspects of the mechanism of splicing given nothing more than a well-annotated genome.