Ectopic Gene Conversions in the Genome of Ten Hemiascomycete Yeast Species
Bibliographic record
Abstract
We characterized ectopic gene conversions in the genome of ten hemiascomycete yeast species. Of the ten species, three diverged prior to the whole genome duplication (WGD) event present in the yeast lineage and seven diverged after it. We analyzed gene conversions from three separate datasets: paralogs from the three pre-WGD species, paralogs from the seven post-WGD species, and common ohnologs from the seven post-WGD species. Gene conversions have similar lengths and frequency and occur between sequences having similar degrees of divergence, in paralogs from pre- and post-WGD species. However, the sequences of ohnologs are both more divergent and less frequently converted than those of paralogs. This likely reflects the fact that ohnologs are more often found on different chromosomes and are evolving under stronger selective pressures than paralogs. Our results also show that ectopic gene conversions tend to occur more frequently between closely linked genes. They also suggest that the mechanisms responsible for the loss of introns in S. cerevisiae are probably also involved in the gene 3'-end gene conversion bias observed between the paralogs of this species.
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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 | 0.001 |
| 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".