Abstract
The purpose of this NSF-Eager grant is to use high-throughput RNA sequencing of the transcriptome to assess the role of alternative splicing in the host-pathogen interaction between Arabidopsis thaliana and Pseudomonas syringae. Although previous studies have demonstrated that alternative splicing plays an important role for individual genes during this interaction, this whole-genome approach will investigate thousands of potential splicing events simultaneously. The method presented here employs a linear models framework to estimate the ratios of known isoforms in a given sample, taking into account the non-uniformity of RNA-sequencing reads along the targeted transcripts. Recently, the method was adapted in order to accommodate paired-end sequencing technology. Briefly, reads are mapped to a transcript catalog (TAIR 10 gene models), partition the reads according to their compatibility with these models, identify reads that are informative for isoform quantification, and then use a linear model to estimate isoform expression ratios for each gene. The results provide a first approximation of the extent of pathogen-induced alternative splicing and so far indicate evidence for a wide variety of novel alternative transcripts. In addition, the set of differentially spliced genes appears to be independent of the set of differentially expressed genes, providing new evidence for a hidden layer of regulation in the transcriptome. Hence, the set of differentially spliced genes provides a promising set of candidate genes that researchers may have previously overlooked by focusing solely on differential gene expression.