Evidence of the adaptive evolution of immune genes in chicken
Bibliographic record
Abstract
The basis for understanding the characteristics of gene functional categories in chicken has been enhanced by the ongoing sequencing of the zebra finch genome, the second bird species to be extensively sequenced. This sequence provides an avian context for examining how variation in chicken has evolved since its divergence from its common ancestor with zebra finch as well as well as a calibrating point for studying intraspecific diversity within chicken. Immune genes have been subject to many selective processes during their evolutionary history: this gene class was investigated here in a set of orthologous chicken and zebra finch genes with functions assigned from the human ortholog. Tests demonstrated that nonsynonymous sites at immune genes were highly conserved both in chicken and on the avian lineage. McDonald-Kreitman tests provided evidence of adaptive evolution and a higher rate of selection on fixation of nonsynonymous substitutions at immune genes compared to that at non-immune genes. Further analyses showed that GC content was much higher in chicken than in zebra finch genes, and was significantly elevated in both species' immune genes. Pathogen challenges are likely to have driven the selective forces that have shaped variation at chicken immune genes, and continue to restrict diversity in this functional class.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".