Masking and purging mutations following EMS treatment in haploid, diploid and tetraploid yeast (<i>Saccharomyces cerevisiae</i>)
Bibliographic record
Abstract
The yeast, Saccharomyces cerevisiae, was used as a model to investigate theories of ploidy evolution. Mutagenesis experiments using the alkylating agent EMS (ethane methyl sulphonate) were conducted to assess the relative importance that masking of deleterious mutations has on response to and recovery from DNA damage. In particular, we tested whether cells with higher ploidy levels have relatively higher fitnesses after mutagenesis, whether the advantages of masking are more pronounced in tetraploids than in diploids, and whether purging of mutations allows more rapid recovery of haploid cells than cells with higher ploidy levels. Separate experiments were performed on asexually propagating stationary phase cells using (1) prototrophic haploid (MAT alpha) and diploid (MATa/alpha) strains and (2) isogenic haploid, diploid and tetraploid strains lacking a functional mating type locus. In both sets of experiments, haploids showed a more pronounced decrease in apparent growth rate than diploids, but both haploids and diploids appeared to recover very rapidly. Tetraploids did not show increased benefits of masking compared with diploids but volume measurements and FACScan analyses on the auxotrophic strains indicated that all treated tetraploid strains decreased in ploidy level and that some of the treated haploid lines increased in ploidy level. Results from these experiments confirm that while masking deleterious mutations provides an immediate advantage to higher ploidy levels in the presence of mutagens, selection is extremely efficient at removing induced mutations, leading growth rates to increase rapidly over time at all ploidy levels. Furthermore, ploidy level is itself a mutable trait in the presence of EMS, with both haploids and tetraploids often evolving towards diploidy (the ancestral state of S. cerevisiae) during the course of the experiment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".