The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation

Abstract

Previous studies have shown that translation elongation is regulated by multiple factors, but the observed heterogeneity remains only partially explained. To dissect quantitatively the different determinants of elongation speed, we use probabilistic modeling to estimate initiation and local elongation rates from ribosome profiling data. This model-based approach allows us to quantify the extent of interference between ribosomes on the same transcript. We show that neither interference nor the distribution of slow codons is sufficient to explain the observed heterogeneity. Instead, we find that electrostatic interactions between the ribosomal exit tunnel and specific parts of the nascent polypeptide govern the elongation rate variation as the polypeptide makes its initial pass through the tunnel. Once the N-terminus has escaped the tunnel, the hydropathy of the nascent polypeptide within the ribosome plays a major role in modulating the speed. We show that our results are consistent with the biophysical properties of the tunnel.

Combinations of slow translating codon clusters can increase mRNA half-life

“…This observation suggests that the presence of mRNA features that give rise to slower initiation rates in a transcript should positively correlate with longer mRNA half-lives. For example, more stable structure near the 5¢ UTR decreases translation-initiation rates (24,25,33). Consistent with this reasoning a strong positive correlation has been reported between the free energy of mRNA folding near the 5¢ UTR and mRNA half-life (34).…”

“…(23). In the results presented we vary the translation-initiation rate α from 0.1 to 0.3 => (21,24,25). We set ./01 and '2345 to 10 =B and 5×10 =E => , respectively, as these rate parameters give the PGK1 mRNA half-lives similar to the ones measured in Ref.…”

Inferring efficiency of translation initiation and elongation from ribosome profiling

“…We base our method on a well-established stochastic model for mRNA translation, the totally asymmetric simple exclusion process (TASEP) 11,28 . Over the years, the model has been improved in many ways to better match real translation 29, 30 and has been repeatedly used to interpret experimental data 16,18,24,[31][32][33][34] .…”

“…We now explain how our method tackles these problems and how it compares to existing methods that have been proposed to infer ribosome dynamics from ribosome profiling data 16,20,22,24 . Our method uses an analytic expression for the ribosome density profile in terms of translation initiation, elongation and termination rates that we recently derived by solving for the steady state of the TASEP in the initiation-limited regime 12, 27 .…”

Transcriptome-wide sites of collided ribosomes reveal principles of translational pausing

“…In combination with quantitative modelling approaches, subsequent studies have identified parameters that can impinge on local translation speed and pausing (reviewed in Schuller and Green (2018)). Among these are, notably, specific amino acids (Charneski and Hurst, 2013), codon pairs (Gamble et al, 2016), tRNA availability (Darnell et al, 2018;Guydosh and Green, 2014), 70 RNA secondary structures (Zhang et al, 2017;Pop et al, 2014), or the folding (Doring et al, 2017) and exit tunnel interactions (Dao Duc and Song, 2018;Charneski and Hurst, 2013) of the nascent peptide. However, to what extent translational pausing occurs in vivo in a mammalian system, which characteristics these pause sites have, and whether they are functionally relevant is still 75 poorly understood.…”