Parental population range expansion before secondary contact promotes heterosis
Bibliographic record
Abstract
AbstractPopulation genomic analysis of hybrid zones is instrumental to our understanding of the evolution of reproductive isolation. Many temperate hybrid zones are formed by the secondary contact between two parental populations that have undergone post-glacial range expansion. Here we show that explicitly accounting for historical parental isolation followed by range expansion prior to secondary contact is fundamental for explaining genetic and fitness patterns in these hybrid zones. Specifically, ancestral population expansion can result in allele surfing where neutral or slightly deleterious mutations drift to high frequency at the expansion front. If these surfed deleterious alleles are recessive, they can contribute to substantial heterosis in hybrids produced at secondary contact, counteracting negative effects of Bateson-Dobzhansky-Muller incompatibilities (BDMIs) hence weakening reproductive isolation. When BDMIs are linked to such recessive deleterious alleles the fitness benefit of introgression at these loci can facilitate introgression at the BDMIs. The extent to which this occurs depends on the strength of selection against the linked deleterious alleles and the distribution of recombination across the chromosome. Finally, surfing of neutral loci can alter the expected pattern of population ancestry, thus accounting for historical population expansion is necessary to develop accurate null genomic models of secondary-contact hybrid zones.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".