Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data

Abstract

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates.

Ribosome Footprint Profiling of Translation throughout the Genome

“…Changes in ribosome occupancy have already revealed elongation defects resulting from molecular (Nedialkova and Leidel, 2015; Zinshteyn and Gilbert, 2013) and physiological (Loayza-Puch et al, 2016) disruptions of translation. Many groups have sought to infer what mRNA features correlate with local variations in ribosome occupancy across a gene in order to learn what factors control the rate of translation elongation (Artieri and Fraser, 2014; Gritsenko et al, 2015; Pop et al, 2014; Reuveni et al, 2011; Shah et al, 2013). These diverse analytical approaches have reached differing conclusions about the impact of codon and amino acid usage on translation speed.…”

“…Computational advances will particularly impact our understanding of the variation in ribosome density across single transcripts and its connection to elongation speed (Artieri and Fraser, 2014; Gardin et al, 2014; Gritsenko et al, 2015; Lareau et al, 2014; Pop et al, 2014; Reuveni et al, 2011; Shah et al, 2013). Occupancy patterns are particularly sensitive to statistical fluctuation and technical biases because they rely on counting small absolute numbers of reads and do not allow averaging over many different positions.…”

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

“…In (161) a novel filter was suggested that enabled estimating the typical codon decoding rate via filtering various problems/phenomena such as pauses/biases/ribosomal traffic jams related to the Ribo-Seq protocol and the translation process. A newer study (163) has suggested inferring the elongation rates and initiation rates of mRNAs by finding parameters that yield the best fitting of the state variables (profiles of local ribosome densities) of the TASEP to the corresponding Ribo-Seq measurements.…”

A Chemical Kinetic Basis for Measuring Translation Initiation and Elongation Rates from Ribosome Profiling data

“…Termination does not influence the cellular concentration of proteins as it is not a rate limiting step [10]. Therefore, knowledge of translation initiation and codon translation rates are important to understand the regulation of gene expression.Significant efforts have been made to extract these rates from data generated from ribosome profiling experiments [11][12][13][14], a technique that measures the relative ribosome density across transcripts [15]. In a number of methods, the actual rates are not measured but instead a ratio of rates, or other relevant quantities have been reported [16][17][18][19][20].…”