Detecting tissue-specific regulation of alternative splicing as a qualitative change in microarray data

Abstract

Alternative splicing has recently emerged as a major mechanism of regulation in the human genome, occurring in perhaps 40-60% of human genes. Thus, microarray studies of functional regulation could, in principle, be extended to detect not only the changes in the overall expression of a gene, but also changes in its splicing pattern between different tissues. However, since changes in the total expression of a gene and changes in its alternative splicing can be mixed in complex ways among a set of samples, separating these effects can be difficult, and is essential for their accurate assessment. We present a simple and general approach for distinguishing changes in alternative splicing from changes in expression, based on detecting systematic anti-correlation between the log-ratios of two different samples versus a pool containing both samples. We have tested this analysis method on microarray data for five human tissues, generated using a standard microarray platform and experimental protocols shown previously to be sensitive to alternative splicing. Our automatic analysis was able to detect a wide variety of tissue-specific alternative splicing events, such as exon skipping,mutually exclusive exons, alternative 3' and alternative 5' splicing, alternative initiation and alternative termination, all of which were validated by independent reverse-transcriptase PCR experiments, with validation rates of 70-85%. Our analysis method also enables hierarchical clustering of genes and samples by the level of similarity to their alternative splicing patterns, revealing patterns of tissue-specific regulation that are distinct from those obtained by hierarchical clustering of gene expression from the same microarray data. Our data and analysis source code are available from http://www.bioinformatics.ucla.edu/ASAP.

Global analysis of alternative splicing during T-cell activation

“…At the early time point, genes regulated at the transcriptional levels are significantly enriched in GO terms associated with immune defense and cytoskeletal functions, whereas genes regulated at the AS level are enriched for GO terms associated with cell-cycle regulation. Independent roles for AS and transcription in the regulation of gene expression programs are consistent with previous results (Le et al 2004;Pan et al 2004Pan et al , 2006. Collectively, these observations suggest that separate mechanisms acting at the AS and transcriptional levels are typically used to achieve distinct functional outcomes in a diverse range of physiological contexts.…”

“…These results raised the question as to the extent of the overlap between genes regulated at the AS and transcript levels in the context of the rapid responses that occur in Jurkat cells following stimulation. In previous studies, we and others observed that different subsets of genes are regulated at the AS and transcript levels in differentiated mammalian tissues (Le et al 2004;Pan et al 2004). Consistent with these previous studies, at both early and late activation points, the majority of the genes that show a change at the level of AS do not show a change at the transcript level (Fig.…”

Quantitative and evolutionary biology of alternative splicing: how changing the mix of alternative transcripts affects phenotypic plasticity and reaction norms

“…Methods for designing and interpreting data from AS-specific arrays (e.g. Le et al, 2004;Shai et al, 2006) are still in their infancy, but it is encouraging to note that there are now companies that state this as their primary goal. Development of methods to examine transcriptome wide changes in AS, in parallel with global gene expression phenotypes, will enable new ways to examine genetic mechanisms and molecular pathways by which variable phenotypes are generated; this in turn will allow examinations of how allelic variation affects plastic responses.…”

Comparative and Functional Analysis of Testis-Specific Genes

“…which have been proven to play critical roles in the process of spermatogenesis and steroidogenesis. Various approaches have been used to analyze these tissueexclusively expressed genes including suppression subtractive hybridization (SSH), 8) differential display reverse transcription-polymerase chain reaction (RT-PCR), 9) microarray, 10) and whole genome approach analysis. 11) The UniGene database (http://www.ncbi.nlm.nih.gov/unigene) is a collection of sequences of individual clones from the cDNA libraries of various organs.…”