ADAPTIVE GAMETE-RECOGNITION DIVERGENCE IN A HYBRIDIZING MYTILUS POPULATION
Bibliographic record
Abstract
Gamete-recognition proteins often evolve rapidly, but it is not known if their divergence occurs within species and corresponds with the evolution of reproductive isolation, or if divergence typically accumulates between already isolated lineages. We examined the evolution of a candidate gamete-recognition protein in several sympatric and allopatric populations of Mytilus blue mussels, species that hybridize in nature. Within a single species, Mytilus galloprovincialis, we found adaptive divergence of Lysin-M7, a sperm acrosomal protein that dissolves the egg vitelline envelope during fertilization. Mytilus galloprovincialis Lysin-M7 alleles group into two distinct clades (termed G and G(D)), and individual alleles in these clades are separated from each other by at least three and up to eleven amino-acid substitutions. Maximum-likelihood estimates of selective pressure (dN/dS =omega) implicate selection in the divergence between M. galloprovincialis Lysin-M7 clades, and within the G(D) clade. Exact tests of population differentiation indicate that the relative frequency of G and G(D) Lysin-M7 alleles differs significantly among M. galloprovincialis populations. Compared with allopatric Mediterranean samples, Lysin-M7 alleles in the G(D) clade are found at elevated frequency in samples from the East Atlantic and California, areas of secondary contact and hybridization between Mytilus species, and Australia, an area of unknown species composition. Adaptive divergence between the alleles most common in allopatry and those found at elevated frequency in samples from sympatry suggests that selection pressures acting in hybridizing populations, likely following Pleistocene secondary contact with M. edulis in the East Atlantic, drove the divergence of Lysin-M7 in M. galloprovincialis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".