Organization and Function of APT, a Subcomplex of the Yeast Cleavage and Polyadenylation Factor Involved in the Formation of mRNA and Small Nucleolar RNA 3′-Ends
Bibliographic record
Abstract
Messenger RNA 3'-end formation is functionally coupled to transcription by RNA polymerase II. By tagging and purifying Ref2, a non-essential protein previously implicated in mRNA cleavage and termination, we isolated a multiprotein complex, holo-CPF, containing the yeast cleavage and polyadenylation factor (CPF) and six additional polypeptides. The latter can form a distinct complex, APT, in which Pti1, Swd2, a type I protein phosphatase (Glc7), Ssu72 (a TFIIB and RNA polymerase II-associated factor), Ref2, and Syc1 are associated with the Pta1 subunit of CPF. Systematic tagging and purification of holo-CPF subunits revealed that yeast extracts contain similar amounts of CPF and holo-CPF. By purifying holo-CPF from strains lacking Ref2 or containing truncated subunits, subcomplexes were isolated that revealed additional aspects of the architecture of APT and holo-CPF. Chromatin immunoprecipitation was used to localize Ref2, Ssu72, Pta1, and other APT subunits on small nucleolar RNA (snoRNA) genes and primarily near the polyadenylation signals of the constitutively expressed PYK1 and PMA1 genes. Use of mutant components of APT revealed that Ssu72 is important for preventing readthrough-dependent expression of downstream genes for both snoRNAs and polyadenylated transcripts. Ref2 and Pta1 similarly affect at least one snoRNA transcript.
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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) | 0.000 | 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 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".