The effects of alternative splicing on transmembrane proteins in the mouse genome.

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Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 02/2004; DOI: 10.1142/9789812704856_0003
Source: PubMed

ABSTRACT Alternative splicing is a major source of variety in mammalian mRNAs, yet many questions remain on its downstream effects on protein function. To this end, we assessed the impact of gene structure and splice variation on signal peptide and transmembrane regions in proteins. Transmembrane proteins perform several key functions in cell signaling and transport, with their function tied closely to their transmembrane architecture. Signal peptides and transmembrane regions both provide key information on protein localization. Thus, any modification to such regions will likely alter protein destination and function. We applied TMHMM and SignalP to a nonredundant set of proteins, and assessed the effects of gene structure and alternative splicing on predicted transmembrane and signal peptide regions. These regions were altered by alternative splicing in roughly half of the cases studied. Transmembrane regions are divided by introns slightly less often than expected given gene structure and transmembrane region size. However, the transmembrane regions in single-pass transmembranes are divided substantially less often than expected. This suggests that intron placement might be subject to some evolutionary pressure to preserve function in these signaling proteins. The data described in this paper is available online at

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    ABSTRACT: Alternative splicing is now recognized as a major mechanism for transcriptome and proteome diversity in higher eukaryotes. Yet, its evolution is poorly understood. Most studies focus on the evolution of exons and introns at the gene level, while only few consider the evolution of transcripts. In this paper, we present a framework for transcript phylogenies where ancestral transcripts evolve along the gene tree by gains, losses, and mutation. We demonstrate the usefulness of our method on a set of 805 genes and two different topics. First, we improve a method for transcriptome reconstruction from ESTs (ASPic), then we study the evolution of function in transcripts. The use of transcript phylogenies allows us to double the specificity of ASPic, whereas results on the functional study reveal that conserved transcripts are more likely to share protein domains than functional sites. These studies validate our framework for the study of evolution in large collections of organisms from the perspective of transcripts; for this purpose, we developed and provide a new tool, TrEvoR.
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