A general definition and nomenclature for alternative splicing events

Abstract

Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is/none of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon/ncontributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of/ndifferent transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the/ndifferent types of reflected splicing variation. In this work, we present a general definition of the AS event along with a/nnotation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns/na specific ‘‘AS code’’ to every possible pattern of splicing variation. On the basis of this definition and the corresponding/ncodes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS/nevents in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity/nacross genes, chromosomes, and species. Our analysis reveals that a substantial part—in human more than a quarter—of/nthe observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and/nto compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that/nproportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and/ncoding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct/nspecific studies investigating the occurrence, impact, and regulation of AS.