Rex1p Deficiency Leads to Accumulation of Precursor Initiator tRNA<sup>Met</sup> and Polyadenylation of Substrate RNAs in <em>Saccharomyces cerevisiae</em>
Bibliographic record
Abstract
A synthetic genetic array was used to identify lethal and slow-growth phenotypes produced when a mutation in TRM6, which encodes a tRNA modification enzyme subunit, was combined with the deletion of any non-essential gene in Saccharomyces cerevisiae. We found that deletion of the REX1 gene resulted in a slow-growth phenotype in the trm6-504 strain. Previously, REX1 was shown to be involved in processing the 3′ ends of 5S rRNA and the dimeric tRNAArg-tRNAAsp. In this study, we have discovered a requirement for Rex1p in processing the 3′ end of tRNAiMet precursors and show that precursor tRNAiMet accumulates in a trm6-504 rex1Δ strain. Loss of Rex1p results in polyadenylation of its substrates, including tRNAiMet, suggesting that defects in 3′ end processing can activate the nuclear surveillance pathway. Finally, purified Rex1p displays Mg2+-dependent ribonuclease activity in vitro, and the enzyme is inactivated by mutation of two highly conserved amino acids.
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.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".