Near-cognate tRNAs dominate codon decoding times in simulated ribosomes

Area of Science:

• Molecular Biology
• Computational Biology
• Genetics

Background:

• Messenger RNA (mRNA) codon sequences are critical for regulating gene expression.
• Ribosome dynamics, translational control, and mRNA stability are influenced by codon sequences.
• Understanding the codon decoding process is essential for comprehending gene expression regulation.

Purpose of the Study:

• To develop and apply an advanced computational modelling tool to study the impact of tRNA species on codon decoding.
• To investigate the sensitivity of codon decoding times to the abundance of cognate, near-cognate, and non-cognate tRNAs.
• To validate the computational model by comparing its predictions with experimental ribosome footprinting data.

Main Methods:

• Utilized computational modelling to simulate the codon decoding process.
• Incorporated tRNA abundance data from Saccharomyces cerevisiae.
• Defined near-cognate tRNAs accurately within the models.
• Parameterized models using high-quality tRNA abundance datasets.
• Compared simulated codon decoding times with experimentally determined ribosome dwell times from ribosome footprinting.

Main Results:

• Simulated codon decoding times were sensitive to the abundance of cognate, near- and non-cognate tRNAs.
• Models accurately defining near-cognate tRNAs and parameterized with quality tRNA abundance data yielded predictions highly similar to experimental ribosome dwell times.
• The study confirmed the significant role of near-cognate tRNAs in codon decoding.

Conclusions:

• The developed computational modelling tools are accurate for studying the codon decoding process.
• Near-cognate tRNAs play a crucial role in modulating codon decoding times and, consequently, translational control.
• This work provides a valuable tool for investigating the intricate relationship between tRNA abundance, codon usage, and gene expression.