Extended stop codon context predicts nonsense codon readthrough efficiency in human cells

Kotchaphorn Mangkalaphiban, Lianwu Fu, Ming Du, Kari Thrasher, Kim M. Keeling, David M. Bedwell and Allan Jacobson ()
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Kotchaphorn Mangkalaphiban: UMass Chan Medical School
Lianwu Fu: The University of Alabama at Birmingham
Ming Du: The University of Alabama at Birmingham
Kari Thrasher: The University of Alabama at Birmingham
Kim M. Keeling: The University of Alabama at Birmingham
David M. Bedwell: The University of Alabama at Birmingham
Allan Jacobson: UMass Chan Medical School

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Protein synthesis terminates when a stop codon enters the ribosome’s A-site. Although termination is efficient, stop codon readthrough can occur when a near-cognate tRNA outcompetes release factors during decoding. Seeking to understand readthrough regulation we used a machine learning approach to analyze readthrough efficiency data from published HEK293T ribosome profiling experiments and compared it to comparable yeast experiments. We obtained evidence for the conservation of identities of the stop codon, its context, and 3’-UTR length (when termination is compromised), but not the P-site codon, suggesting a P-site tRNA role in readthrough regulation. Models trained on data from cells treated with the readthrough-promoting drug, G418, accurately predicted readthrough of premature termination codons arising from CFTR nonsense alleles that cause cystic fibrosis. This predictive ability has the potential to aid development of nonsense suppression therapies by predicting a patient’s likelihood of improvement in response to drugs given their nonsense mutation sequence context.

Date: 2024
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DOI: 10.1038/s41467-024-46703-z

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