Mutator genes for suppression of gross chromosomal rearrangements identified by a genome-wide screening in <i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
Different types of gross chromosomal rearrangements (GCRs), including translocations, interstitial deletions, terminal deletions with de novo telomere additions, and chromosome fusions, are observed in many cancers. Multiple pathways, such as S-phase checkpoints, DNA replication, recombination, chromatin remodeling, and telomere maintenance that suppress GCRs have been identified. To experimentally expand our knowledge of other pathway(s) that suppress GCRs, we developed a generally applicable genome-wide screening method. In this screen, we identified 10 genes (ALO1, CDC50, CSM2, ELG1, ESC1, MMS4, RAD5, RAD18, TSA1, and UFO1) that encode proteins functioning in the suppression of GCRs. Moreover, the breakpoint junctions of GCRs from these GCR mutator mutants were determined with modified breakpoint-mapping methods. We also identified nine genes (AKR1, BFR1, HTZ1, IES6, NPL6, RPL13B, RPL27A, RPL35A, and SHU2) whose mutations generated growth defects with the pif1Delta mutation. In addition, we found that some of these mutations changed the telomere size.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".