Widespread Adaptive Introgression of Major Histocompatibility Complex Genes across Vertebrate Hybrid Zones
Bibliographic record
Abstract
Interspecific introgression is a potentially important source of novel variation of adaptive significance. Although multiple cases of adaptive introgression are well documented, broader generalizations about its targets and mechanisms are lacking. Multiallelic balancing selection, particularly when acting through rare allele advantage, is an evolutionary mechanism expected to favor adaptive introgression. This is because introgressed alleles are likely to confer an immediate selective advantage, facilitating their establishment in the recipient species even in the face of strong genomic barriers to introgression. Vertebrate major histocompatibility complex genes are well-established targets of long-term multiallelic balancing selection, so widespread adaptive major histocompatibility complex introgression is expected. Here, we evaluate this hypothesis using data from 29 hybrid zones formed by fish, amphibians, squamates, turtles, birds, and mammals at advanced stages of speciation. The key prediction of more extensive major histocompatibility complex introgression compared to genome-wide introgression was tested with three complementary statistical approaches. We found evidence for widespread adaptive introgression of major histocompatibility complex genes, providing a link between the process of adaptive introgression and an underlying mechanism. Our work identifies major histocompatibility complex introgression as a general mechanism by which species can acquire novel, and possibly regain previously lost, variation that may enhance defense against pathogens and increase adaptive potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".