Abstract
Quantitative prediction on protein synthesis requires accurate translation initiation and codon translation rates. Ribosome profiling data, which provide steady-state distribution of relative ribosome occupancies along a transcript, can be used to extract these rate parameters. Various methods have been developed in the past few years to measure translation-initiation and codon translation rates from ribosome profiling data. In the review, we provide a detailed analysis of the key methods employed to extract the translation rate parameters from ribosome profiling data. We further discuss how these approaches were used to decipher the role of various structural and sequence-based features of mRNA molecules in the regulation of gene expression. The utilization of these accurate rate parameters in computational modeling of protein synthesis may provide new insights into the kinetic control of the process of gene expression.
Highlights
Protein molecules carry out a vast array of biological functions
Quantitative Modeling of Protein Synthesis parameters using ribosome profiling data (Weinberg et al, 2016; Duc and Song, 2018; Sharma et al, 2019). The analysis of these translation rate parameters and their use in protein synthesis simulations have started unraveling the sophisticated mechanism that nature has developed to optimize the use of cellular resources (Tuller et al, 2010; Diament et al, 2018; Lyu et al, 2020). In this mini-review, we provide the brief overview of a few recently developed methods that extract translation rate parameters from ribosome profiling data
Many computational tools can convert this time-independent steady-state information into the kinetic rate parameters of protein synthesis (Dana and Tuller 2014; Pop et al, 2014; Szavits-Nossan and Ciandrini, 2020). Analysis of these rate parameters and their use in protein synthesis simulations give significant insight into the translational regulation of an individual gene (Shah et al, 2013; Lyu et al, 2020). These rate parameters help identify various structural and sequence-based mRNA features that control the rate of protein synthesis (Weinberg et al, 2016; Duc et al, 2018; Sharma et al, 2019)
Summary
Protein molecules carry out a vast array of biological functions. almost every cellular process, from genome regulation to energy metabolism, requires a unique set of proteins with their precise concentration in a cell (Berg et al, 2002; Miyazaki and Esser, 2009). Quantitative Modeling of Protein Synthesis parameters using ribosome profiling data (Weinberg et al, 2016; Duc and Song, 2018; Sharma et al, 2019) The analysis of these translation rate parameters and their use in protein synthesis simulations have started unraveling the sophisticated mechanism that nature has developed to optimize the use of cellular resources (Tuller et al, 2010; Diament et al, 2018; Lyu et al, 2020). In this mini-review, we provide the brief overview of a few recently developed methods that extract translation rate parameters from ribosome profiling data. This mini-review aims to promote the use of big biological data sets among biophysicists, biophysical chemists and system biologist to achieve greater accuracy and reliability in the quantitative modeling of protein synthesis
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