Visualising ribosome profiling and using it for reading frame detection and exploration of eukaryotic translation initiation

Ribosome profiling (ribo-seq) is a recently developed technique that provides genomewide information on protein synthesis (GWIPS) in vivo. The high resolution of ribo-seq is one of the exciting properties of this technique. In Chapter 2, I present a computational method that utilises the sub-codon precision and triplet periodicity of ribosome profiling data to detect transitions in the translated reading frame. Application of this method to ribosome profiling data generated for human HeLa cells allowed us to detect several human genes where the same genomic segment is translated in more than one reading frame. Since the initial publication of the ribosome profiling technique in 2009, there has been a proliferation of studies that have used the technique to explore various questions with respect to translation. A review of the many uses and adaptations of the technique is provided in Chapter 1. Indeed, owing to the increasing popularity of the technique and the growing number of published ribosome profiling datasets, we have developed GWIPS-viz (http://gwips.ucc.ie), a ribo-seq dedicated genome browser. Details on the development of the browser and its usage are provided in Chapter 3. One of the surprising findings of ribosome profiling of initiating ribosomes carried out in 3 independent studies, was the widespread use of non-AUG codons as translation initiation start sites in mammals. Although initiation at non-AUG codons in mammals has been documented for some time, the extent of non-AUG initiation reported by these ribo-seq studies was unexpected. In Chapter 4, I present an approach for estimating the strength of initiating codons based on the leaky scanning model of translation initiation. Application of this approach to ribo-seq data illustrates that initiation at non-AUG codons is inefficient compared to initiation at AUG codons. In addition, our approach provides a probability of initiation score for each start site that allows its strength of initiation to be evaluated.

Comparative survey of the relative impact of mRNA features on local ribosome profiling read density

Ribosome profiling (Ribo-seq), a promising technology for exploring ribosome decoding rates, is characterized by the presence of infrequent high peaks in ribosome footprint density and by long alignment gaps. Here, to reduce the impact of data heterogeneity we introduce a simple normalization method, Ribo-seq Unit Step Transformation (RUST). RUST is robust and outperforms other normalization techniques in the presence of heterogeneous noise. We illustrate how RUST can be used for identifying mRNA sequence features that affect ribosome footprint densities globally. We show that a few parameters extracted with RUST are sufficient for predicting experimental densities with high accuracy. Importantly the application of RUST to 30 publicly available Ribo-seq data sets revealed a substantial variation in sequence determinants of ribosome footprint frequencies, questioning the reliability of Ribo-seq as an accurate representation of local ribosome densities without prior quality control. This emphasizes our incomplete understanding of how protocol parameters affect ribosome footprint densities.