The Hidden Complexity of Mendelian Traits across Natural Yeast Populations
Bibliographic record
Abstract
Mendelian traits are considered to be at the lower end of the complexity spectrum of heritable phenotypes. However, more than a century after the rediscovery of Mendel's law, the global landscape of monogenic variants, as well as their effects and inheritance patterns within natural populations, is still not well understood. Using the yeast Saccharomyces cerevisiae, we performed a species-wide survey of Mendelian traits across a large population of isolates. We generated offspring from 41 unique parental pairs and analyzed 1,105 cross/trait combinations. We found that 8.9% of the cases were Mendelian. Further tracing of causal variants revealed background-specific expressivity and modified inheritances, gradually transitioning from Mendelian to complex traits in 30% of the cases. In fact, when taking into account the natural population diversity, the hidden complexity of traits could be substantial, confounding phenotypic predictability even for simple Mendelian traits.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".