The importance of nonsense errors: Estimating the rates and implications of ribosome drop-off during protein synthesis

The process of translation is both energetically costly and relatively error-prone compared to transcription and replication. Nonsense errors during translation occur when a ribosome drops off a transcript before reaching a stop codon, resulting in energetic investment in an incomplete and likely non-functional protein. Nonsense errors impose a potentially significant energy burden on the cell, making it critical to quantify their frequency and energetic cost. Here, we present a model of ribosome movement for estimating protein production, elongation, and nonsense error rates from high-throughput ribosome profiling data. Applying this model to an exemplary ribosome profiling dataset in S. cerevisiae, we find that nonsense error rates vary substantially between codons and that these types of errors place an energetic burden on cells comparable to ribosome pausing. Overall, we present multiple lines of evidence that selection against nonsense errors is a prominent force shaping protein-coding sequence evolution and codon usage bias, in particular.

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Journal
PLoS Genetics
Published
2026-06-09
DOI
https://doi.org/10.1371/journal.pgen.1012162
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.00

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article

The importance of nonsense errors: Estimating the rates and implications of ribosome drop-off during protein synthesis

Alexander L. Cope, Michael A. Gilchrist, Denizhan Pak
PLoS Genetics
RNA and protein synthesis mechanisms
article

The importance of nonsense errors: Estimating the rates and implications of ribosome drop-off during protein synthesis

Alexander L. Cope, Michael A. Gilchrist, Denizhan Pak
article en

Abstract

The process of translation is both energetically costly and relatively error-prone compared to transcription and replication. Nonsense errors during translation occur when a ribosome drops off a transcript before reaching a stop codon, resulting in energetic investment in an incomplete and likely non-functional protein. Nonsense errors impose a potentially significant energy burden on the cell, making it critical to quantify their frequency and energetic cost. Here, we present a model of ribosome movement for estimating protein production, elongation, and nonsense error rates from high-throughput ribosome profiling data. Applying this model to an exemplary ribosome profiling dataset in S. cerevisiae, we find that nonsense error rates vary substantially between codons and that these types of errors place an energetic burden on cells comparable to ribosome pausing. Overall, we present multiple lines of evidence that selection against nonsense errors is a prominent force shaping protein-coding sequence evolution and codon usage bias, in particular.

PLoS GeneticsVol. 22(6)
Rutgers, The State University of New Jersey (US), National Institute for Mathematical and Biological Synthesis (US), Johnson University (US), Indiana University Bloomington (US), University of Tennessee at Knoxville (US)
National Institute of General Medical Sciences
Openalex Percentile: Top 10%
RNA and protein synthesis mechanisms
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