RPA guides UNG to uracil in ssDNA to facilitate antibody class switching and repair of mutagenic uracil at the replication fork
Bibliographic record
Abstract
Activation-induced cytidine deaminase (AID) interacts with replication protein A (RPA), the major ssDNA-binding protein, to promote deamination of cytosine to uracil in transcribed immunoglobulin (Ig) genes. Uracil-DNA glycosylase (UNG) acts in concert with AID during Ig diversification. In addition, UNG preserves genome integrity by base-excision repair (BER) in the overall genome. How UNG is regulated to support both mutagenic processing and error-free repair remains unknown. UNG is expressed as two isoforms, UNG1 and UNG2, which both contain an RPA-binding helix that facilitates uracil excision from RPA-coated ssDNA. However, the impact of this interaction in antibody diversification and genome maintenance has not been investigated. Here, we generated B-cell clones with targeted mutations in the UNG RPA-binding motif, and analysed class switch recombination (CSR), mutation frequency (5' Ig Sμ), and genomic uracil in clones representing seven Ung genotypes. We show that the UNG:RPA interaction plays a crucial role in both CSR and repair of AID-induced uracil at the Ig loci. By contrast, the interaction had no significant impact on total genomic uracil levels. Thus, RPA coordinates UNG during CSR and pre-replicative repair of mutagenic uracil in ssDNA but is not essential in post-replicative and canonical BER of uracil in dsDNA.
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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 | 0.001 |
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".