Life without RNAi: noncoding RNAs and their functions in <i>Saccharomyces cerevisiae</i>This paper is one of a selection of papers published in this Special Issue, entitled 30th Annual International Asilomar Chromatin and Chromosomes Conference, and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
There are a number of well-characterized and fundamental roles for noncoding RNAs (ncRNAs) in gene regulation in all kingdoms of life. ncRNAs, such as ribosomal RNAs, transfer RNAs, small nuclear RNAs, small nucleolar RNAs, and small interfering RNAs, can serve catalytic and scaffolding functions in transcription, messenger RNA processing, translation, and RNA degradation. Recently, our understanding of gene expression has been dramatically challenged by the identification of large and diverse populations of novel ncRNAs in the eukaryotic genomes surveyed thus far. Studies carried out using the budding yeast Saccharomyces cerevisiae indicate that at least some coding genes are regulated by these novel ncRNAs. S. cerevisiae lacks RNA interference (RNAi) and, thus, provides an ideal system for studying the RNAi-independent mechanisms of ncRNA-based gene regulation. The current picture of gene regulation is one of great unknowns, in which the transcriptional environment surrounding a given locus may have as much to do with its regulation as its DNA sequence or local chromatin structure. Drawing on the recent research in S. cerevisiae and other organisms, this review will discuss the identification of ncRNAs, their origins and processing, and several models that incorporate ncRNAs into the regulation of gene expression and chromatin structure.
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 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 | 0.001 | 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) | 0.002 | 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 teacher head, 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".