ArticleGenome biology and evolution2022
Stop Codon Usage as a Window into Genome Evolution: Mutation, Selection, Biased Gene Conversion and the TAG Paradox.
Article in Genome biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A predictive framework for stop-loss variants with C-terminal extensions.Nucleic acids research · 2026Article
- Virome metatranscriptomic profiling of birch pollen reveals a diverse viral community.Frontiers in plant science · 2026Article
- Life at the extremes: maximally divergent microbes with similar genomic signatures linked to extreme environments.NAR genomics and bioinformatics · 2025Article
- Article
- Lost in translation: conserved amino acid usage despite extreme codon bias in foraminifera.mBio · 2025Article
- Multiple independent genetic code reassignments of the UAG stop codon in phyllopharyngean ciliates.PLoS genetics · 2024Article
- Comparative genomics of two protozoansHeliyon · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein coding genes terminate with one of three stop codons (TAA, TGA, or TAG) that, like synonymous codons, are not employed equally. With TGA and TAG having identical nucleotide content, analysis of their differential usage provides an unusual window into the forces operating on what are ostensibly functionally identical residues. Across genomes and between isochores within the human genome, TGA usage increases with G + C content but, with a common G + C → A + T mutation bias, this cannot be explained by mutation bias-drift equilibrium. Increased usage of TGA in G + C-rich genomes or genomic regions is also unlikely to reflect selection for the optimal stop codon, as TAA appears to be universally optimal, probably because it has the lowest read-through rate. Despite TAA being favored by selection and mutation bias, as with codon usage bias G + C pressure is the prime determinant of between-species TGA usage trends. In species with strong G + C-biased gene conversion (gBGC), such as mammals and birds, the high usage and conservation of TGA is best explained by an A + T → G + C repair bias. How to explain TGA enrichment in other G + C-rich genomes is less clear. Enigmatically, across bacterial and archaeal species and between human isochores TAG usage is mostly unresponsive to G + C pressure. This unresponsiveness we dub the TAG paradox as currently no mutational, selective, or gBGC model provides a well-supported explanation. That TAG does increase with G + C usage across eukaryotes makes the usage elsewhere yet more enigmatic. We suggest resolution of the TAG paradox may provide insights into either an unknown but common selective preference (probably at the DNA/RNA level) or an unrecognized complexity to the action of gBGC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.