Mutability and mutational spectrum of chromosome transmission fidelity genes
Why this work is in the frame
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Bibliographic record
Abstract
It has been more than two decades since the original chromosome transmission fidelity (Ctf) screen of Saccharomyces cerevisiae was published. Since that time the spectrum of mutations known to cause Ctf and, more generally, chromosome instability (CIN) has expanded dramatically as a result of systematic screens across yeast mutant arrays. Here we describe a comprehensive summary of the original Ctf genetic screen and the cloning of the remaining complementation groups as efforts to expand our knowledge of the CIN gene repertoire and its mutability in a model eukaryote. At the time of the original screen, it was impossible to predict either the genes and processes that would be overrepresented in a pool of random mutants displaying a Ctf phenotype or what the entire set of genes potentially mutable to Ctf would be. We show that in a collection of 136 randomly selected Ctf mutants, >65% of mutants map to 13 genes, 12 of which are involved in sister chromatid cohesion and/or kinetochore function. Extensive screening of systematic mutant collections has shown that ~350 genes with functions as diverse as RNA processing and proteasomal activity mutate to cause a Ctf phenotype and at least 692 genes are required for faithful chromosome segregation. The enrichment of random Ctf alleles in only 13 of ~350 possible Ctf genes suggests that these genes are more easily mutable to cause genome instability than the others. These observations inform our understanding of recurring CIN mutations in human cancers where presumably random mutations are responsible for initiating the frequently observed CIN phenotype of tumors.
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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 it