Statistical approaches for analysis of ribosome profiling data: regulation of stop codon readthrough during protein translation

Supervisor: Heejung Shim

Available for: MSc and undergraduate research projects.

Location: Melbourne Integrative Genomics, University of Melbourne

Project title: Statistical approaches for analysis of ribosome profiling data: regulation of stop codon readthrough during protein translation

Background: Protein translation is an intricate process precisely controlled to ensure accurate protein production. One key rule of protein translation is that the translation elongation complex exits the transcript when it reaches the first in frame stop codon. Stop codon readthrough has been considered as rare mistakes. Recently, the advance of genome technology has started generating results pointing to evidence of programed stop codon readthrough of unknown biological significance (Dunn et al. 2013; Lindblad-Toh et al. 2011). More importantly, a stop codon readthrough isoform of VEGF is recently discovered and found to play an antagonist role in angiogenesis (Eswarappa et al. 2014). This discovery highlighted potential biological roles of stop codon readthrough translation. Using the fine structure pattern in ribosome profiling data, we have developed a method to identify coding regions that are translated transcriptome-wide (Raj et al. 2016).

Proposed project: The goal of the current project is to adapt the existing methodology to identify translation readthrough events and to further evaluate potential biological importance of these events. Further association mapping using existing data to identify genetic variants associated with stop codon readthrough is likely to reveal mechanistic insights on regulation of this process.