Based on recent studies, including transcriptome-scale ribosome profiling, it is likely that the regulation of gene expression at the level of protein translation initiation is more important than previously realized. We are investigating translation initiation in the budding yeast model system through a combination of mass spectrometry, molecular genetic, and bioinformatics approaches. Improved understanding of the repertoire of translation initiation events of genes in yeast and higher organisms will provide fuller annotations of proteomes, and will be particularly useful for functional interpretation of future large datasets of mRNA sequences, especially in analyses of mRNA sequence variants and mutations associated with disease states.

Our primary goal is to assess the repertoire of protein products of genes contributed by different translation initiation events. We would like to know how common it is for genes to have multiple translation initiation sites, potentially giving rise to different protein products or overlapping products with alternative amino termini. Mechanisms giving rise to alternative amino termini could include leaky initiation at alternative start sites or translation recoding mechanisms such as frameshifts. Individual cases of leaky initiation and recoding have been described in yeast and other higher organisms.

In collaboration with Professor Michael Rice in Mathematics and Computer Science, we are using information theoretic and machine learning approaches to analyze translation initiation. We are investigating how mRNA properties including sequence context and predicted RNA structure contribute to translation initiation.