Detecting translational regulation by change point analysis of ribosome profiling datasets

Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and gene isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4 , but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new gene isoforms.