Synonymous codon usage is subject to selection in thermophilic bacteria
Bibliographic record
Abstract
The patterns of synonymous codon usage, both within and among genomes, have been extensively studied over the past two decades. Despite the accumulating evidence that natural selection can shape codon usage, it has not been possible to link a particular pattern of codon usage to a specific external selective force. Here, we have analyzed the patterns of synonymous codon usage in 40 completely sequenced prokaryotic genomes. By combining the genes from several genomes (more than 80 000 genes in all) into a single dataset for this analysis, we were able to investigate variations in codon usage, both within and between genomes. The results show that synonymous codon usage is affected by two major factors: (i) the overall G+C content of the genome and (ii) growth at high temperature. This study focused on the relationship between synonymous codon usage and the ability to grow at high temperature. We have been able to eliminate both phylogenetic history and lateral gene transfer as possible explanations for the characteristic pattern of codon usage among the thermophiles. Thus, these results demonstrate a clear link between a particular pattern of codon usage and an external selective force.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".