Adenine Enrichment at the Fourth CDS Residue in Bacterial Genes Is Consistent with Error Proofing for +1 Frameshifts

Abrahams, Liam; Hurst, Laurence D.

doi:10.1093/molbev/msx223

Cited by 7 publications

(11 citation statements)

References 168 publications

(199 reference statements)

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“…This has been supported by bioinformatic studies of stop codon usage in gene locations other than that of the canonical stop. For example, it has been suggested that adenine enrichment at the fourth coding sequence residue in bacterial genes may promote translation termination following a frameshift event at the initiating ATG that allows an out-of-frame stop codon to be read [9, 10]. In 5’ leading regions, in-frame stop codons are enriched and postulated to rapidly terminate premature translations [11] (i.e.…”

Section: Introductionmentioning

confidence: 99%

In eubacteria, unlike eukaryotes, there is no evidence for selection favouring fail-safe 3’ additional stop codons

Hurst

2019

PLoS Genet

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Errors throughout gene expression are likely deleterious, hence genomes are under selection to ameliorate their consequences. Additional stop codons (ASCs) are in-frame nonsense ‘codons’ downstream of the primary stop which may be read by translational machinery should the primary stop have been accidentally read through. Prior evidence in several eukaryotes suggests that ASCs are selected to prevent potentially-deleterious consequences of read-through. We extend this evidence showing that enrichment of ASCs is common but not universal for single cell eukaryotes. By contrast, there is limited evidence as to whether the same is true in other taxa. Here, we provide the first systematic test of the hypothesis that ASCs act as a fail-safe mechanism in eubacteria, a group with high read-through rates. Contra to the predictions of the hypothesis we find: there is paucity, not enrichment, of ASCs downstream; substitutions that degrade stops are more frequent in-frame than out-of-frame in 3’ sequence; highly expressed genes are no more likely to have ASCs than lowly expressed genes; usage of the leakiest primary stop (TGA) in highly expressed genes does not predict ASC enrichment even compared to usage of non-leaky stops (TAA) in lowly expressed genes, beyond downstream codon +1. Any effect at the codon immediately proximal to the primary stop can be accounted for by a preference for a T/U residue immediately following the stop, although if anything, TT- and TC- starting codons are preferred. We conclude that there is no compelling evidence for ASC selection in eubacteria. This presents an unusual case in which the same error could be solved by the same mechanism in eukaryotes and prokaryotes but is not. We discuss two possible explanations: that, owing to the absence of nonsense mediated decay, bacteria may solve read-through via gene truncation and in eukaryotes certain prion states cause raised read-through rates.

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Section: Introductionmentioning

confidence: 99%

In eubacteria, unlike eukaryotes, there is no evidence for selection favouring fail-safe 3’ additional stop codons

Hurst

2019

PLoS Genet

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“…This is, in other words, mutationally driven . Conversely, enrichment for adenine at specific sites is thought to reduce the impact of ribosomal frame‐shift events due to introduction of out‐of‐frame stop codons, as modeled using bacterial genomes (Abrahams & Hurst, 2017 ) (i.e., driven by selection ). Other types of nucleotide biases are also described, such as the 70% GC content of the rubella virus genome (Zhou et al, 2012 ), largely attributed to the use of C bases at degenerate positions(Zhou et al, 2012 ).…”

Section: Types Of Genome Compositional Biasmentioning

confidence: 99%

Compositional biases in RNA viruses: Causes, consequences and applications

Gaunt

Digard

2021

WIREs RNA

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If each of the four nucleotides were represented equally in the genomes of viruses and the hosts they infect, each base would occur at a frequency of 25%. However, this is not observed in nature. Similarly, the order of nucleotides is not random (e.g., in the human genome, guanine follows cytosine at a frequency of ~0.0125, or a quarter the number of times predicted by random representation). Codon usage and codon order are also nonrandom. Furthermore, nucleotide and codon biases vary between species. Such biases have various drivers, including cellular proteins that recognize specific patterns in nucleic acids, that once triggered, induce mutations or invoke intrinsic or innate immune responses. In this review we examine the types of compositional biases identified in viral genomes and current understanding of the evolutionary mechanisms underpinning these trends. Finally, we consider the potential for large scale synonymous recoding strategies to engineer RNA virus vaccines, including those with pandemic potential, such as influenza A virus and Severe Acute Respiratory Syndrome Coronavirus Virus 2. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein‐RNA Recognition

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“…This pattern corresponds to codons that are recognized by rare tRNA species at the start of the mRNA transcript, together with downstream codons that are translated by abundant tRNA species. This codon pattern causes ribosomes to 'stack' at the start of the mRNA in that region, directing translation of the first 30-50 residues and then efficiently translating the remaining sequence encoded by optimal codons [34,35]. This phenomenon results from an over-representation of nonoptimal, low-efficiency codons [e.g., AGT, TCA (Ser), CAT (His), GTA (Val), and ATA (Ile)] at the beginning of CDSs [34,35].…”

Section: A B C D E Fmentioning

confidence: 99%

Non‐optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts

et al. 2021

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Circulating animal coronaviruses occasionally infect humans. The SARS‐CoV‐2 is responsible for the current worldwide outbreak of COVID‐19 that has resulted in 2 112 844 deaths as of late January 2021. We compared genetic code preferences in 496 viruses, including 34 coronaviruses and 242 corresponding hosts, to uncover patterns that distinguish single‐ and ‘promiscuous’ multiple‐host‐infecting viruses. Based on a codon usage preference score, promiscuous viruses were shown to significantly employ nonoptimal codons, namely codons that involve ‘wobble’ binding to anticodons, as compared to single‐host viruses. The codon adaptation index (CAI) and the effective number of codons (ENC) were calculated for all viruses and hosts. Promiscuous viruses were less adapted hosts vs single‐host viruses (P‐value = 4.392e‐11). All coronaviruses exploit nonoptimal codons to infect multiple hosts. We found that nonoptimal codon preferences at the beginning of viral coding sequences enhance the translational efficiency of viral proteins within the host. Finally, coronaviruses lack endogenous RNA degradation motifs to a significant degree, thereby increasing viral mRNA burden and infection load. To conclude, we found that promiscuously infecting coronaviruses prefer nonoptimal codon usage to remove degradation motifs from their RNAs and to dramatically increase their viral RNA production rates.

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Adenine Enrichment at the Fourth CDS Residue in Bacterial Genes Is Consistent with Error Proofing for +1 Frameshifts

Cited by 7 publications

References 168 publications

In eubacteria, unlike eukaryotes, there is no evidence for selection favouring fail-safe 3’ additional stop codons

In eubacteria, unlike eukaryotes, there is no evidence for selection favouring fail-safe 3’ additional stop codons

Compositional biases in RNA viruses: Causes, consequences and applications

Non‐optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts

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