Repetitive sequence variation and dynamics in the ribosomal DNA array of <i>Saccharomyces cerevisiae</i> as revealed by whole-genome resequencing
Bibliographic record
Abstract
Ribosomal DNA (rDNA) plays a key role in ribosome biogenesis, encoding genes for the structural RNA components of this important cellular organelle. These genes are vital for efficient functioning of the cellular protein synthesis machinery and as such are highly conserved and normally present in high copy numbers. In the baker's yeast Saccharomyces cerevisiae, there are more than 100 rDNA repeats located at a single locus on chromosome XII. Stability and sequence homogeneity of the rDNA array is essential for function, and this is achieved primarily by the mechanism of gene conversion. Detecting variation within these arrays is extremely problematic due to their large size and repetitive structure. In an attempt to address this, we have analyzed over 35 Mbp of rDNA sequence obtained from whole-genome shotgun sequencing (WGSS) of 34 strains of S. cerevisiae. Contrary to expectation, we find significant rDNA sequence variation exists within individual genomes. Many of the detected polymorphisms are not fully resolved. For this type of sequence variation, we introduce the term partial single nucleotide polymorphism, or pSNP. Comparative analysis of the complete data set reveals that different S. cerevisiae genomes possess different patterns of rDNA polymorphism, with much of the variation located within the rapidly evolving nontranscribed intergenic spacer (IGS) region. Furthermore, we find that strains known to have either structured or mosaic/hybrid genomes can be distinguished from one another based on rDNA pSNP number, indicating that pSNP dynamics may provide a reliable new measure of genome origin and stability.
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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".