Purifying Selection in the Toll-Like Receptors of Song Sparrows Melospiza melodia
Bibliographic record
Abstract
Variation in immune gene sequences is known to influence resistance to infectious diseases and parasites, and hence survival and mate choice, across animal taxa. Toll-like receptors (TLRs) comprise one essential gene family in the vertebrate innate immune system and recognize evolutionarily conserved structures from all major microorganism classes. However, the causes and consequences of TLR variation in passerine birds remain largely unexplored. We examined 7 TLR genes in song sparrows (Melospiza melodia), a species that is studied across North America. We then examined sequences from 4 unduplicated TLRs (TLR1LB, TLR3, TLR4, and TLR15) from birds in 2 parts of the species' range (N = 27, N = 6), tested for evidence of selection, and conducted pilot analyses of the role of TLR heterozygosity in survival. We identified 45 SNPs: 19 caused changes in amino acid sequences and 2 of these were likely deleterious. We found no evidence of codon-level episodic positive selection but detected purifying selection at codons in all TLRs. Contrary to expectations we found no strong correlation between heterozygosity at TLRs and inbreeding coefficient f (estimate ± standard error [SE] = -0.68 ± 0.37, Radj2 = 0.08, F1,25 = 3.38, P = 0.08). In addition, pilot analyses revealed no relationship between TLR heterozygosity and survival (β ± SE: 0.09 ± 2.00, P = 0.96), possibly due to small sample size. Further analyses of genetic diversity in TLRs are likely to advance understanding of the effects of innate immune gene diversity on the fitness and persistence of wild populations.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".