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Updated: Jun 30, 2025

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
Extended stop codon context predicts nonsense codon readthrough efficiency in human cells
Kotchaphorn Mangkalaphiban1,2, Lianwu Fu3, Ming Du3
1Department of Microbiology and Physiological Systems, UMass Chan Medical School, 368 Plantation Street, Worcester, MA, 01655, USA.
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.
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