Abstract

Errors in gene transcription can be costly, and organisms have evolved to prevent their occurrence or mitigate their costs. The simplest interpretation of the drift barrier hypothesis suggests that species with larger population sizes would have lower transcriptional error rates. However, Escherichia coli seems to have a higher transcriptional error rate than species with lower effective population sizes, for example Saccharomyces cerevisiae. This could be explained if selection in E. coli were strong enough to maintain adaptations that mitigate the consequences of transcriptional errors through robustness, on a gene by gene basis, obviating the need for low transcriptional error rates and associated costs of global proofreading. Here, we note that if selection is powerful enough to evolve local robustness, selection should also be powerful enough to locally reduce error rates. We therefore predict that transcriptional error rates will be lower in highly abundant proteins on which selection is strongest. However, we only expect this result when error rates are high enough to significantly impact fitness. As expected, we find such a relationship between expression and transcriptional error rate for non-C→U errors in E. coli (especially G→A), but not in S. cerevisiae. We do not find this pattern for C→U changes in E. coli, presumably because most deamination events occurred during sample preparation, but do for C→U changes in S. cerevisiae, supporting the interpretation that C→U error rates estimated with an improved protocol, and which occur at rates comparable with E. coli non-C→U errors, are biological.

Highlights

  • IntroductionWe expect natural selection to reduce their rate. selection cannot achieve everything

  • Errors are costly, and we expect natural selection to reduce their rate

  • The Cir-Seq technique is effective in preventing sequencing errors from inflating estimated mistranscription rates (Acevedo and Andino 2014), it does not eliminate artifacts of the sample preparation and analysis such as mutations occurring during the Cir-Seq experiment, nor inaccurate mapping of reads to the genome

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Summary

Introduction

We expect natural selection to reduce their rate. selection cannot achieve everything. It is only able to purge deleterious mutations when their selection coefficient s is significantly greater than one divided by the “effective population size.”. This numerical limit to selection may reflect not just the number of individuals in a population, and competing selection at linked sites (Lynch 2007; Good and Desai 2014). Codon usage bias is stronger in species believed to have higher effective population sizes (Vicario et al 2007), indicating stronger selection to purge slightly deleterious synonymous mutations

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