Bioinformatics analysis of alternative splicing.
Over the past few years, the analysis of alternative splicing using bioinformatics has emerged as an important new field, and has significantly changed our view of genome function. One exciting front has been the analysis of microarray data to measure alternative splicing genome-wide. Pioneering studies of both human and mouse data have produced algorithms for discerning evidence of alternative splicing and clustering genes and samples by their alternative splicing patterns. Moreover, these data indicate the presence of alternative splice forms in up to 80 per cent of human genes. Comparative genomics studies in both mammals and insects have demonstrated that alternative splicing can in some cases be predicted directly from comparisons of genome sequences, based on heightened sequence conservation and exon length. Such studies have also provided new insights into the connection between alternative splicing and a variety of evolutionary processes such as Alu-based exonisation, exon creation and loss. A number of groups have used a combination of bioinformatics, comparative genomics and experimental validation to identify new motifs for splice regulatory factors, analyse the balance of factors that regulate alternative splicing, and propose a new mechanism for regulation based on the interaction of alternative splicing and nonsense-mediated decay. Bioinformatics studies of the functional impact of alternative splicing have revealed a wide range of regulatory mechanisms, from NAGNAG sites that add a single amino acid; to short peptide segments that can play surprisingly complex roles in switching protein conformation and function (as in the Piccolo C2A domain); to events that entirely remove a specific protein interaction domain or membrane anchoring domain. Common to many bioinformatics studies is a new emphasis on graph representations of alternative splicing structures, which have many advantages for analysis.
Lee
Christopher
C
Molecular Biology Institute, Center for Genomics and Proteomics, Dept. of Chemistry & Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095-1570, USA. leec@mbi.ucla.edu
Wang
Qi
Q
D000465:Algorithms; D017398:Alternative Splicing / Q000235:genetics*; D000818:Animals; D002874:Chromosome Mapping / Q000379:methods*; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D020869:Gene Expression Profiling / Q000379:methods* / Q000639:trends; D005786:Gene Expression Regulation / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D014157:Transcription Factors / Q000502:physiology
D014157:Transcription Factors