A Comparison of Synonymous Codon Usage Bias Patterns in DNA and RNA Virus Genomes: Quantifying the Relative Importance of Mutational Pressure and Natural Selection
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Bibliographic record
Abstract
Codon usage bias patterns have been broadly explored for many viruses. However, the relative importance of mutation pressure and natural selection is still under debate. In the present study, I tried to resolve controversial issues on determining the principal factors of codon usage patterns for DNA and RNA viruses, respectively, by examining over 38000 ORFs. By utilizing variation partitioning technique, the results showed that 27% and 21% of total variation could be attributed to mutational pressure, while 5% and 6% of total variation could be explained by natural selection for DNA and RNA viruses, respectively, in codon usage patterns. Furthermore, the combined effect of mutational pressure and natural selection on influencing codon usage patterns of viruses is substantial (explaining 10% and 8% of total variation of codon usage patterns). With respect to GC variation, GC content is always negatively and significantly correlated with aromaticity. Interestingly, the signs for the significant correlations between GC, gene lengths, and hydrophobicity are completely opposite between DNA and RNA viruses, being positive for DNA viruses while being negative for RNA viruses. At last, GC12 versus G3s plot suggests that natural selection is more important than mutational pressure on influencing the GC content in the first and second codon positions.
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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) | 0.000 | 0.000 |
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 it