RNA-seq datasets can contain millions of intron reads per library that are typically removed from downstream analysis. Only reads overlapping annotated exons are considered to be informative since mature mRNA is assumed to be the major component sequenced, especially for poly(A) RNA libraries. In this study, we show that intron reads are informative, and through exploratory data analysis of read coverage that intron signal is representative of both pre-mRNAs and intron retention. We demonstrate how intron reads can be utilized in differential expression analysis using our index method where a unique set of differentially expressed genes can be detected using intron counts. In exploring read coverage, we also developed the superintronic software that quickly and robustly calculates user-defined summary statistics for exonic and intronic regions. Across multiple datasets, superintronic enabled us to identify several genes with distinctly retained introns that had similar coverage levels to that of neighbouring exons. The work and ideas presented in this paper is the first of its kind to consider multiple biological sources for intron reads through exploratory data analysis, minimizing bias in discovery and interpretation of results. Our findings open up possibilities for further methods development for intron reads and RNA-seq data in general.

RNA-seq datasets can contain millions of intron reads per sequenced library that are typically removed from downstream analysis. Only reads overlapping annotated exons are considered to be informative since mature mRNA is assumed to be the major component sequenced, especially when examining poly(A) RNA samples. By examining multiple datasets, we demonstrate that intron reads are informative and that signal is shared between exon and intron counts. The majority of expressed genes contain reads in both exon and intron regions, where exon and intron log-counts are positively correlated. On a per gene basis intron counts are larger in Total RNA libraries than the same biological sample sequenced under a poly(A) RNA protocol. This is due to 3' coverage bias in poly(A) RNA libraries affecting medium to long intron regions, where a considerable drop in read coverage for introns residing at the 5' end of genes is observed. Looking across thousands of genes simultaneously we characterise coverage profiles of exon and intron regions in poly(A) RNA and Total RNA libraries. Our study provides a general yet comprehensive examination into intron reads that is insightful and applicable to transcriptomics research, especially in the identification of pre-mRNA levels, transcript structure and intron retention detection.