Nej1 interacts with Sae2 at DNA double-stranded breaks to inhibit DNA resection
Bibliographic record
Abstract
The two major pathways of DNA double-strand break repair, nonhomologous end-joining and homologous recombination, are highly conserved from yeast to mammals. The regulation of 5'-DNA resection controls repair pathway choice and influences repair outcomes. Nej1 was first identified as a canonical NHEJ factor involved in stimulating the ligation of broken DNA ends, and more recently, it was shown to participate in DNA end-bridging and in the inhibition of 5'-resection mediated by the nuclease/helicase complex Dna2-Sgs1. Here, we show that Nej1 interacts with Sae2 to impact DSB repair in three ways. First, we show that Nej1 inhibits interaction of Sae2 with the Mre11-Rad50-Xrs2 complex and Sae2 localization to DSBs. Second, we found that Nej1 inhibits Sae2-dependent recruitment of Dna2 independently of Sgs1. Third, we determined that NEJ1 and SAE2 showed an epistatic relationship for end-bridging, an event that restrains broken DNA ends and reduces the frequency of genomic deletions from developing at the break site. Finally, we demonstrate that deletion of NEJ1 suppressed the synthetic lethality of sae2Δ sgs1Δ mutants, and that triple mutant viability was dependent on Dna2 nuclease activity. Taken together, these findings provide mechanistic insight to how Nej1 functionality inhibits the initiation of DNA resection, a role that is distinct from its involvement in end-joining repair at DSBs.
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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) | 0.000 | 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 | 0.001 |
| 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".