Dyskerin: an essential pseudouridine synthase with multifaceted roles in ribosome biogenesis, splicing, and telomere maintenance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dyskerin and its homologs are ancient and conserved enzymes that catalyze the most common post-transcriptional modification found in cells, pseudouridylation. The resulting pseudouridines provide stability to RNA molecules and regulate ribosome biogenesis and splicing events. Dyskerin does not act independently—it is the core component of a protein heterotetramer, which associates with RNAs that contain the H/ACA motif. The variety of H/ACA RNAs that guide the function of this ribonucleoprotein (RNP) complex highlights the diversity of cellular processes in which dyskerin participates. When associated with small nucleolar (sno) RNAs, it regulates ribosomal (r) RNAs and ribosome biogenesis. By interacting with small Cajal body (sca) RNAs, it targets small nuclear (sn) RNAs to regulate pre-mRNA splicing. As a component of the telomerase holoenzyme, dyskerin binds to the telomerase RNA to modulate telomere maintenance. In a disease context, dyskerin malfunction can result in multiple detrimental phenotypes. Mutations in DKC1 , the gene that encodes dyskerin, cause the premature aging syndrome X-linked dyskeratosis congenita (X-DC), a still incurable disorder that typically leads to bone marrow failure. In this review, we present the classical and most recent findings on this essential protein, discussing the evolutionary, structural, and functional aspects of dyskerin and the H/ACA RNP. The latest research underscores the role that dyskerin plays in the regulation of gene expression, translation efficiency, and telomere maintenance, along with the impacts that defective dyskerin has on aging, cell proliferation, haematopoietic potential, and cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it