Balancing selection and introgression of newt immune-response genes
Bibliographic record
Abstract
The importance of interspecific introgression as a source of adaptive variation is increasingly recognized. Theory predicts that beneficial genetic variants cross species boundaries easily even when interspecific hybridization is rare and gene flow is strongly constrained throughout the genome. However, it remains unclear whether certain classes of genes are particularly prone to adaptive introgression. Genes affected by balancing selection (BS) may constitute such a class, because forms of BS that favour novel, initially rare alleles, should facilitate introgression. We tested this hypothesis in hybridizing newts by comparing 13 genes with signatures of BS, in particular an excess of common non-synonymous polymorphisms, to the genomic background (154 genes). Parapatric hybridizing taxa were less differentiated in BS candidate genes than more closely related allopatric lineages, while the opposite was observed in the control genes. Coalescent and forward simulations that explored neutral and BS scenarios under isolation and migration showed that processes other than differential gene flow are unlikely to account for this pattern. We conclude that BS, probably involving a form of novel allele advantage, promotes introgression. This mechanism may be a source of adaptively relevant variation in hybridizing species over prolonged periods.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".