Detecting translational regulation by change point analysis of ribosome profiling data sets

Abstract

Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosomedensity is constant along the length of the mRNA coding region, this can be altered in response to translational regulatoryevents. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosomeprofiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density shouldoccur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells andshowed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introducedby deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes inribosome density present in individual mRNA ribosome profiles. Additional sequence and gene isoform information obtained fromthe UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. Inparticular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoproteinmRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful foridentification of new transcript isoforms.