Effects of dyskeratosis congenita mutations in dyskerin, NHP2 and NOP10 on assembly of H/ACA pre-RNPs
Bibliographic record
Abstract
Dyskeratosis congenita (DC) is a rare genetic syndrome that gives rise to a variety of disorders in affected individuals. Remarkably, all causative gene mutations identified to date share a link to telomere/telomerase biology. We found that the most prevalent dyskerin mutation in DC (A353V) did not affect formation of the NAF1-dyskerin-NOP10-NHP2 tetramer that normally assembles with nascent H/ACA RNAs in vivo. However, the A353V mutation slightly reduced pre-RNP assembly with the H/ACA-like domain of human telomerase RNA (hTR). In contrast, NHP2 mutations V126M and Y139H impaired association with NOP10, leading to major pre-RNP assembly defects with all H/ACA RNAs tested, including the H/ACA domain of hTR. Mutation R34W in NOP10 caused no apparent defect in protein tetramer formation, but it severely affected pre-RNP assembly with the H/ACA domain of hTR and a subset of H/ACA RNAs. Surprisingly, H/ACA sno/scaRNAs that encode miRNAs were not affected by the mutation R34W, and they were able to form pre-RNPs with NOP10-R34W. This indicates structural differences between H/ACA RNPs that encode miRNAs and those that do not. Altogether, our results suggest that, in addition to major defects in the telomere/telomerase pathways, some of the disorders occurring in DC may be caused by alteration of most H/ACA RNPs, or by only a subset of them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".