Natural Selection Determines Synonymous Codon Usage Patterns of Neuraminidase (NA) Gene of the Different Subtypes of Influenza A Virus in Canada
Bibliographic record
Abstract
Synonymous codon usage patterns of neuraminidase (NA) gene of 64 subtypes (one is a mixed subtype) of influenza A virus found in Canada were analyzed. In total, 1422 NA sequences were analyzed. Among the subtypes, H1N1 is the prevailing one with 516 NCBI accession records, followed by H3N2, H3N8, and H4N6. The year of 2009 has the highest report records for the NA sequences in Canada, corresponding to the 2009 pandemic event. Correspondence analysis on the RSCU values of the four major subtypes showed that they had distinct clustering patterns in the two-dimensional scatter plot, indicating that different subtypes of IAV utilized different preferential codons. This subtype clustering pattern implied the important influence of natural selection, which could be further evidenced by an extremely flattened regression line in the neutrality plot (GC12 versus G3s plot) and a significant phylogenetic signal on the distribution of different subtypes in the clades of the phylogenetic tree ( λ statistic). In conclusion, different subtypes of IAV showed an evolutionary differentiation on choosing different optimal codons. Natural selection played a deterministic role to structure IAV codon usage patterns in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".