Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments

摘要: Alternative splicing, polyadenylation of pre-messenger RNA molecules and differential promoter usage can produce a variety transcript isoforms whose respective expression levels are regulated in time space, thus contributing specific biological functions. However, the repertoire mammalian alternative transcripts their regulation still poorly understood. Second-generation sequencing is now opening unprecedented routes to address analysis entire transcriptomes. Here, we developed methods that allow prediction quantification derived solely from exon RNA-Seq data. These based on an explicit statistical model enable within or between conditions using any known gene annotation, as well relative structures. Applying these human dataset, validated significant fraction predictions by RT-PCR. Data further showed correlated with information originating junction reads. A direct comparison arrays indicated improved performances over microarrays skipped exons. Altogether, set presented here comprehensively addresses multiple aspects isoform analysis. The software available open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/.