Conditional Genetic Interactions of<i>RTT107</i>,<i>SLX4</i>, and<i>HRQ1</i>Reveal Dynamic Networks upon DNA Damage in<i>S. cerevisiae</i>
Bibliographic record
Abstract
The DNA damage response (DDR) is a dynamic process that is crucial for protecting the cell from challenges to genome integrity. Although many genome-wide studies in Saccharomyces cerevisiae have identified genes that contribute to resistance to DNA-damaging agents, more work is needed to elucidate the changes in genetic interaction networks in response to DNA lesions. Here we used conditional epistatic miniarray profiling to analyze the genetic interaction networks of the DDR genes RTT107, SLX4, and HRQ1 under three DNA-damaging conditions: camptothecin, hydroxyurea, and methyl methanesulfonate. Rtt107 and its interaction partner Slx4 are targets of the checkpoint kinase Mec1, which is central to the DDR-signaling cascades. Hrq1 recently was identified as a novel member of the RecQ helicase family in S. cerevisiae but is still poorly characterized. The conditional genetic networks that we generated revealed functional insights into all three genes and showed that there were varied responses to different DNA damaging agents. We observed that RTT107 had more genetic interactions under camptothecin conditions than SLX4 or HRQ1, suggesting that Rtt107 has an important role in response to this type of DNA lesion. Although RTT107 and SLX4 function together, they also had many distinct genetic interactions. In particular, RTT107 and SLX4 showed contrasting genetic interactions for a few genes, which we validated with independently constructed strains. Interestingly, HRQ1 had a genetic interaction profile that correlated with that of SLX4 and both were enriched for very similar gene ontology terms, suggesting that they function together in the DDR.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".