title: Splicing predictions reliably classify different types of alternative splicing.
abstract: Alternative splicing is a key player in the creation of complex mammalian transcriptomes and its misregulation is associated with many human diseases. Multiple mRNA isoforms are generated from most human genes, a process mediated by the interplay of various RNA signature elements and trans-acting factors that guide spliceosomal assembly and intron removal. Here, we introduce a splicing predictor that evaluates hundreds of RNA features simultaneously to successfully differentiate between exons that are constitutively spliced, exons that undergo alternative 5' or 3' splice-site selection, and alternative cassette-type exons. Surprisingly, the splicing predictor did not feature strong discriminatory contributions from binding sites for known splicing regulators. Rather, the ability of an exon to be involved in one or multiple types of alternative splicing is dictated by its immediate sequence context, mainly driven by the identity of the exon's splice sites, the conservation around them, and its exon/intron architecture. Thus, the splicing behavior of human exons can be reliably predicted based on basic RNA sequence elements.
authors: Department of Microbiology and Molecular Genetics, University of California, Irvine, California 92697-4025, USA Institute of Molecular Biology (IMB), D-55128 Mainz, Germany.
authors: Anke
authors: A
authors: Busch
authors: Department of Microbiology and Molecular Genetics, University of California, Irvine, California 92697-4025, USA.
authors: Klemens J
authors: KJ
authors: Hertel
mesh_terms: D017398:Alternative Splicing; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005091:Exons; D005815:Genetic Code; D006801:Humans; D008322:Mammals / Q000235:genetics; D022821:RNA Splice Sites / Q000235:genetics*; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA
chemical_list: D022821:RNA Splice Sites
keywords: alternative splicing; bioinformatics; splicing predictor; support vector machine