Asymmetric Diversification of Mating Pheromones in Fission Yeast
Bibliographic record
Abstract
Abstract In fungi, mating between partners critically depends on the molecular recognition of two peptidyl mating pheromones by their respective receptors. The fission yeast Schizosaccharomyces pombe has two mating types, Plus (P) and Minus (M), which secrete two different mating pheromones: P-factor recognized by Mam2, and M-factor recognized by Map3, respectively. Our recent study demonstrated that a few mutations in both M-factor and Map3 can trigger reproductive isolation, a cause of speciation, in S. pombe . Here we explored the mechanism underlying reproductive isolation through genetic changes of pheromones and receptors. We investigated the diversity of genes encoding the pheromones and their receptor in 150 S. pombe wild 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). We also explored the recognition specificity of pheromones between S. pombe (Sp) and its close relative Schizosaccharomyces octosporus (So). 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, allowing them to mate successfully. Thus, recognition of M-factor seems to be tight, whereas that of P-factor is relatively loose. Moreover, diversity of P-factor and Mam2 might be due to a P-factor-specific peptidase. Overall, the asymmetric system for pheromone recognition in yeasts seems to allow flexible adaptation to mutational changes in the combination of pheromone and receptor while maintaining tight recognition for mating partners.
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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) | 0.001 | 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".