Asymmetric diversification of mating pheromones in fission yeast
Bibliographic record
Abstract
In fungi, mating between partners depends on the molecular recognition of two peptidyl mating pheromones by their respective receptors. The fission yeast Schizosaccharomyces pombe (Sp) has two mating types, Plus (P) and Minus (M). The mating pheromones P-factor and M-factor, secreted by P and M cells, are recognized by the receptors mating type auxiliary minus 2 (Mam2) and mating type auxiliary plus 3 (Map3), respectively. Our recent study demonstrated that a few mutations in both M-factor and Map3 can trigger reproductive isolation in S. pombe. Here, we explored the mechanism underlying reproductive isolation through genetic changes of pheromones/receptors in nature. We investigated the diversity of genes encoding the pheromones and their receptor in 150 wild S. pombe strains. Whereas the amino acid sequences of M-factor and Map3 were completely conserved, those of P-factor and Mam2 were very diverse. In addition, the P-factor gene contained varying numbers of tandem repeats of P-factor (4-8 repeats). By exploring the recognition specificity of pheromones between S. pombe and its close relative Schizosaccharomyces octosporus (So), we found that So-M-factor did not have an effect on S. pombe P cells, but So-P-factor had a partial effect on S. pombe M cells. Thus, recognition of M-factor seems to be stringent, whereas that of P-factor is relatively relaxed. We speculate that asymmetric diversification of the two pheromones might be facilitated by the distinctly different specificities of the two receptors. Our findings suggest that M-factor communication plays an important role in defining the species, whereas P-factor communication is able to undergo a certain degree of flexible adaptation-perhaps as a first step toward prezygotic isolation in S. pombe.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".