Patterns of Diversity and Spatial Variability of β-Defensin Innate Immune Genes in a Declining Wild Population of Tree Swallows
Bibliographic record
Abstract
Assessing the genetic variation and distribution of immune genes across heterogeneous environmental conditions in wild species is essential to further our understanding of the role of pathogen pressure and potential resistance or prevalence in hosts. Researchers have recently investigated β-defensin genes in the wild, because their variability suggests that they may play an important role in innate host defense. This study investigated the variation occurring at 6 innate immune genes of the β-defensin family in a declining population of tree swallows (Tachycineta bicolor) in southern Québec, Canada (N = 160). We found that all 6 genes showed synonymous and nonsynonymous single nucleotide polymorphisms (SNPs) within the exon coding for the mature peptide. These results indicated that this group of genes was diverse in tree swallows. Our results suggested a potential interaction of this group of genes with fluctuating pathogen diversity, however, we found no sign of positive or negative selection. We assessed whether or not the distribution of genetic diversity of β-defensin genes in our study population differed between 2 regions that strongly differ in their level of agricultural intensification. Adults are highly philopatric to their breeding sites and their immunological responses differ between these 2 regions. However, we found little evidence that the level and distribution of genetic variability differed between these heterogeneous environmental conditions. Further studies should aim to assess the link between genetic diversity of β-defensin genes and fitness-related traits in 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 | 0.001 |
| Science and technology studies | 0.001 | 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".