High-Resolution Genetic Mapping With Ordered Arrays of <i>Saccharomyces cerevisiae</i> Deletion Mutants
Bibliographic record
Abstract
We present a method for high-resolution genetic mapping that takes advantage of the ordered set of viable gene deletion mutants, which form a set of colinear markers covering almost every centimorgan of the Saccharomyces cerevisiae genome, and of the synthetic genetic array (SGA) system, which automates the construction of double mutants formed by mating and meiotic recombination. The Cbk1 kinase signaling pathway, which consists minimally of CBK1, MOB2, KIC1, HYM1, and TAO3 (PAG1), controls polarized morphogenesis and activation of the Ace2 transcription factor. Deletion mutations in the Cbk1 pathway genes are tolerated differently by common laboratory strains of S. cerevisiae, being viable in the W303 background but dead in the S288C background. Genetic analysis indicated that the lethality of Cbk1 pathway deletions in the S288C background was suppressed by a single allele specific to the W303 background. SGA mapping (SGAM) was used to locate this W303-specific suppressor to the SSD1 locus, which contains a known polymorphism that appears to compromise SSD1 function. This procedure should map any mutation, dominant or recessive, whose phenotype is epistatic to wild type, that is, a phenotype that can be scored from a mixed population of cells obtained by germination of both mutant and wild-type spores. In principle, SGAM should be applicable to the analysis of multigenic traits. Large-scale construction of ordered mutations in other model organisms would broaden the application of this approach.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".