The evolutionary dynamics of alternative splicing during primate neuronal differentiation

Alternative splicing (AS) is emerging as an important regulatory process for complex biological processes such as neuronal differentiation. To uncover the functional consequences of AS during neuronal differentiation we performed a comparative transcriptomic analysis using human, rhesus, chimpanzee and orangutan pluripotent stem cells. Transcriptomic studies commonly involve the identification and quantification of alternative processing events, but the need for predicting the functional consequences of changes to the relative inclusion of alternative events remains largely unaddressed. Many tools exist for the former task, albeit often limited to rudimentary event types. Few tools exist for the latter task; each with significant limitations. To address these issues we developed junctionCounts, which captures both simple and complex pairwise AS events and quantifies them with straightforward exon-exon and exon-intron junction reads in RNA-seq data, performing competently among similar tools in terms of sensitivity, false discovery and quantification accuracy. Its partner utility, cdsInsertion identifies transcript coding sequence information, including the presence of premature termination codons, gathered via in silico translation from annotated start codons. It then couples transcript-level information to AS events to predict functional effects, i.e. nonsense-mediated decay (NMD). We used junctionCounts and related tools to discover both conserved and species-specific splicing dynamics as well as regulation of NMD during differentiation. Our work demonstrates this tools capacity to robustly characterize AS and bridge the gap of predicting its potential effect on mRNA isoform fate. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/581203v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@17b2be4org.highwire.dtl.DTLVardef@17e8992org.highwire.dtl.DTLVardef@79e47forg.highwire.dtl.DTLVardef@888161_HPS_FORMAT_FIGEXP M_FIG C_FIG junctionCounts is an alternative splicing analysis tool that identifies both simple and complex splicing events from a gene annotation and then measures their percent spliced-in from mapped RNA-seq junction reads.