Analysis of rRNA Synthesis using Quantitative Transcription Run-on (qTRO) in Yeast
Bibliographic record
Abstract
Comparative transcriptional analyses require appropriate and precise normalization. Here we describe a modified transcription run-on (TRO) method, named quantitative TRO (qTRO), that allows quantification of nascent transcription activity. The most critical improvement it introduces is a new standardization method for RNA isolation and hybridization steps, enabling transcription activity quantification and comparative biological analysis. We used this technique with chromatin immunoprecipitation to investigate RNA polymerase I (RNAPI) transcription activity and its rDNA gene profiles in Saccharomyces cerevisiae. We designed a set of new oligonucleotide probes complementary to nascent ribosomal RNA (rRNA) transcripts and standardized their hybridization strength. The qTRO method could be successfully implemented to study RNAPI transcription in response to oxidative stress and in two mutant strains with impaired rRNA synthesis.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".