Revealing Global Regulatory Features of Mammalian Alternative Splicing Using a Quantitative Microarray Platform (original) (raw)
Related papers
Omics A Journal of Integrative Biology, 2008
Alternative splicing generates functional diversity in higher organisms through alternative first and last exons, skipped and included exons, intron retentions and alternative donor, and acceptor sites. In large-scale microarray studies in humans and the mouse, emphasis so far has been placed on exon-skip events, leaving the prevalence and importance of other splice types largely unexplored. Using a new human splice variant database and a genomewide microarray to probes thousands of splice events of each type, we measured differential expression of splice types across six pair of diverse cell lines and validated the database annotation process. Results suggest that splicing in humans is more complex than simple exon-skip events, which account for a minority of splicing differences. The relative frequency of differential expression of the splice types correlates with what is found by our annotation efforts. In conclusion, alternative splicing in human cells is considerably more complex than the canonical example of the exon skip. The complementary approaches of genome-wide annotation of alternative splicing in human and design of genome-wide splicing microarrays to measure differential splicing in biological samples provide a powerful high-throughput tool to study the role of alternative splicing in human biology.
BMC Bioinformatics, 2008
Background: Over 60% of protein-coding genes in vertebrates express mRNAs that undergo alternative splicing. The resulting collection of transcript isoforms poses significant challenges for contemporary biological assays. For example, RT-PCR validation of gene expression microarray results may be unsuccessful if the two technologies target different splice variants. Effective use of sequence-based technologies requires knowledge of the specific splice variant(s) that are targeted. In addition, the critical roles of alternative splice forms in biological function and in disease suggest that assay results may be more informative if analyzed in the context of the targeted splice variant.
ASPicDB: A database resource for alternative splicing analysis
Bioinformatics, 2008
Motivation: Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. Results: ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation.
BMC Genetics, 2009
Background: Commercially available microarrays have been used in many settings to generate expression profiles for a variety of applications, including target selection for disease detection, classification, profiling for pharmacogenomic response to therapeutics, and potential disease staging. However, many commercially available microarray platforms fail to capture transcript diversity produced by alternative splicing, a major mechanism for driving proteomic diversity through transcript heterogeneity. Results: The human Genome-Wide SpliceArray™ (GWSA), a novel microarray platform, utilizes an existing probe design concept to monitor such transcript diversity on a genome scale. The human GWSA allows the detection of alternatively spliced events within the human genome through the use of exon body and exon junction probes to provide a direct measure of each transcript, through simple calculations derived from expression data. This report focuses on the performance and validation of the array when measured against standards recently published by the Microarray Quality Control (MAQC) Project. The array was shown to be highly quantitative, and displayed greater than 85% correlation with the HG-U133 Plus 2.0 array at the gene level while providing more extensive coverage of each gene. Almost 60% of splice events among genes demonstrating differential expression of greater than 3 fold also contained extensive splicing alterations. Importantly, almost 10% of splice events within the gene set displaying constant overall expression values had evidence of transcript diversity. Two examples illustrate the types of events identified: LIM domain 7 showed no differential expression at the gene level, but demonstrated deregulation of an exon skip event, while erythrocyte membrane protein band 4.1-like 3 was differentially expressed and also displayed deregulation of a skipped exon isoform. Conclusion: Significant changes were detected independent of transcriptional activity, indicating that the controls for transcript generation and transcription are distinct, and require novel tools in order to detect changes in specific transcript quantity. Our results demonstrate that the SpliceArray™ design will provide researchers with a robust platform to detect and quantify specific changes not only in overall gene expression, but also at the individual transcript level.