Physical and Functional Interaction Between Fanconi Anemia Group J Helicase and MRE11 Nuclease
Bibliographic record
Abstract
FANCJ mutations are linked to the chromosomal instability disorder Fanconi anemia (FA) and increase breast cancer risk. FANCJ encodes a DNA helicase implicated in homologous recombination (HR) repair of double‐strand breaks (DSBs) and interstrand cross‐links (ICLs), but its mechanism of action is not well understood. Live cell imaging demonstrates that FANCJ recruitment to laser‐induced DSBs, but not psoralen‐ICLs, is dependent on nuclease‐active MRE11 and independent of BRCA1. Inhibition of MRE11 nuclease by Mirin adversely affected FANCJ localization to laser‐induced DSBs, but not psoralen‐ICLs. FANCJ is required for timely recruitment of Bloom's syndrome helicase and CtIP to DSBs in vivo. FANCJ directly interacts with MRE11 and inhibits its exonuclease activity in a specific manner, suggesting that FANCJ harnesses MRE11 nuclease to facilitate DSB processing and appropriate end resection. Spontaneous or IR‐induced chromosomal instability in FANCJ‐depleted cells is suppressed when MRE11 is depleted. Interplay between FANCJ and MRE11 insures a normal response to IR‐induced DSBs, whereas FANCJ involvement in ICL repair is regulated by MLH1 and FANCA, but not FANCD2. Thus, MRE11 helps to recruit FANCJ to DSBs and FANCJ can modulate MRE11 nuclease activity at DNA ends, consistent with a collaborative role of FANCJ and BLM helicases with MRE11 in strand resection.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".