Genome-wide Profiling of RNA splicing in prostate tumor from RNA-seq data using virtual microarrays

Genome-wide profiling of alternative splicing is not new. Before the invent of RNA-Seq technologies, genome-wide profiling of RNA splicing in biological samples included exon arrays, splice junction arrays, and genome-wide tiling arrays. Use of these technologies to profile known splicing events in various biological contexts has already revealed the importance of splicing in cancer research. A recent review of genome-wide profiling of splicing in cancer using various microarray platforms suggests that splicing in cancer is prevalent, regulated and that novel therapeutic strategies are emerging.

The success of microarrays in profiling known splicing in cancer can be extended to identifying tumor specific splicing events in reads from RNA-Seq using virtual microarray experiments. In such an experiment, short RNA reads from RNA-Seq can be considered virtual equivalent of cellular RNA, in silico mapping of reads can be considered virtual equivalent of hybridization and the sequences of exon-exon junction probes equivalent of virtual microarray platform. Hence, a non-redundant reference database of known splice junctions can be used to directly map RNA reads to detect and measure expression levels of known splice events. Although such an approach is limited to detection, by augmenting the database with predicted junctions, one could also infuse discovery into this approach.

Here, researchers at the Institute of Bioinformatics and Applied Biotechnology, Bangalore, India have profiled less than a million known plus predicted splice events to identify tumor-specific splicing in prostate tumor using a RNA-Seq dataset of matched tumor-normal from ten individuals downloaded from NCBI public repository.

  • Srinivasan S, Patil AH, Verma M, Bingham JL, Srivatsan R. (2012) Genome-wide Profiling of RNA splicing in prostate tumor from RNA-seq data using virtual microarrays. J of Clin Bioinform [Epub ahead of print]. [article]
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