Large-scale analysis of transcript data reveals thousands of recursive splicing events in human introns
Abstract
Recursive splicing (RS) is a process in which an intron is removed from a nascent RNA molecule in two or more splicing events rather than one. We introduce a novel approach for detecting recursive splice sites (RSSs), the intronic loci at which RS events occur, based on alignment of total RNA-seq data to short, customized “target” sequences. We applied this approach to a data set from a recent study of gene expression in the human brain, using parameters corresponding to a very low false discovery rate, and found 3,022 RSSs that appear in 2,775 distinct introns from 2,407 genes. 2,891 (96%) of these RSSs are in protein-coding genes. The median length of recursively spliced introns from this set is 10,114 base pairs, which is substantially longer than the median human intron, but much shorter than average RS intron lengths reported in prior studies. Our work dramatically increases the number of known RSSs in the human genome and provides a generalizable bioinformatics pipeline for annotating RSSs from total RNA-seq data. Author Summary RNA splicing is a necessary step in the processing of most eukaryotic RNA molecules. Sometimes splicing includes an intermediate step known as “recursive splicing,” through which introns are split into two subintrons, each of which is independently excised by the splicing machinery. Over the last decade, several studies have attempted to catalog recursive splice sites in humans and other model organisms, achieving little agreement across methods. While previous studies primarily used targeted laboratory methods, we sought to leverage previously generated large-scale human RNA-sequencing data sets to identify recursive splice sites. We specifically used a data set of total RNA-seq data, which contains many premature transcripts that are only partially spliced. We developed a method based on two parallel read alignment steps using both spliced and unspliced alignments of these reads. We found 3022 high-confidence recursive splice sites, which represents a 30-fold increase as compared to the largest prior curated set.