Uncoupling Splicing From Transcription Using Antisense Oligonucleotides Reveals a Dual Role for I Exon Donor Splice Sites in Antibody Class Switching
Bibliographic record
Abstract
) locus. During CSR, transcription through specific switch (S) regions and processing of non-coding germline transcripts (GLTs) are essential for the targeting of activation-induced cytidine deaminase (AID). While CSR to IgG1 is abolished in mice lacking an Iγ1 exon donor splice site (dss), many questions remain regarding the importance of I exon dss recognition in CSR. To further clarify the role of I exon dss in CSR, we first evaluated RNA polymerase II (RNA pol II) loading and chromatin accessibility in S regions after activation of mouse B cells lacking Iγ1 dss. We found that deletion of Iγ1 dss markedly reduced RNA pol II pausing and active chromatin marks in the Sγ1 region. We then challenged the post-transcriptional function of I exon dss in CSR by using antisense oligonucleotides (ASOs) masking I exon dss on GLTs. Treatment of stimulated B cells with an ASO targeting Iγ1 dss, in the acceptor Sγ1 region, or Iμ dss, in the donor Sμ region, did not decrease germline transcription but strongly inhibited constitutive splicing and CSR to IgG1. Supporting a global effect on CSR, we also observed that the targeting of Iμ dss reduced CSR to IgG3 and, to a lesser extent, IgG2b isotypes. Altogether, this study reveals that the recognition of I exon dss first supports RNA pol II pausing and the opening of chromatin in targeted S regions and that GLT splicing events using constitutive I exon dss appear mandatory for the later steps of CSR, most likely by guiding AID to S regions.
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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".