Chromatin- and Transcription-Related Factors Repress Transcription from within Coding Regions throughout the Saccharomyces cerevisiae Genome
Bibliographic record
Abstract
Previous studies in Saccharomyces cerevisiae have demonstrated that cryptic promoters within coding regions activate transcription in particular mutants. We have performed a comprehensive analysis of cryptic transcription in order to identify factors that normally repress cryptic promoters, to determine the amount of cryptic transcription genome-wide, and to study the potential for expression of genetic information by cryptic transcription. Our results show that a large number of factors that control chromatin structure and transcription are required to repress cryptic transcription from at least 1,000 locations across the S. cerevisiae genome. Two results suggest that some cryptic transcripts are translated. First, as expected, many cryptic transcripts contain an ATG and an open reading frame of at least 100 codons. Second, several cryptic transcripts are translated into proteins. Furthermore, a subset of cryptic transcripts tested is transiently induced in wild-type cells following a nutritional shift, suggesting a possible physiological role in response to a change in growth conditions. Taken together, our results demonstrate that, during normal growth, the global integrity of gene expression is maintained by a wide range of factors and suggest that, under altered genetic or physiological conditions, the expression of alternative genetic information may occur.
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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) | 0.001 | 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".