The identification of FANCD2 DNA binding domains reveals nuclear localization sequences
Bibliographic record
Abstract
Fanconi anemia (FA) is a recessive genetic disorder characterized by congenital abnormalities, progressive bone-marrow failure, and cancer susceptibility. The FA pathway consists of at least 21 FANC genes (FANCA-FANCV), and the encoded protein products interact in a common cellular pathway to gain resistance against DNA interstrand crosslinks. After DNA damage, FANCD2 is monoubiquitinated and accumulates on chromatin. FANCD2 plays a central role in the FA pathway, using yet unidentified DNA binding regions. By using synthetic peptide mapping and DNA binding screen by electromobility shift assays, we found that FANCD2 bears two major DNA binding domains predominantly consisting of evolutionary conserved lysine residues. Furthermore, one domain at the N-terminus of FANCD2 bears also nuclear localization sequences for the protein. Mutations in the bifunctional DNA binding/NLS domain lead to a reduction in FANCD2 monoubiquitination and increase in mitomycin C sensitivity. Such phenotypes are not fully rescued by fusion with an heterologous NLS, which enable separation of DNA binding and nuclear import functions within this domain that are necessary for FANCD2 functions. Collectively, our results enlighten the importance of DNA binding and NLS residues in FANCD2 to activate an efficient FA pathway.
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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) | 0.001 | 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".