Mononucleotide repeats represent an important source of polymorphic microsatellite markers in <i>Aspergillus nidulans</i>
Bibliographic record
Abstract
In fungi, microsatellites occur less frequently throughout the genome and tend to be less polymorphic compared with other organisms. Most studies that develop microsatellites for fungi focus on dinucleotide and trinucleotide repeats, and thus mononucleotide repeats, which are much more abundant in fungal genomes, may represent an overlooked resource. This study examined the relative probabilities of polymorphism in mononucleotide, dinucleotide and trinucleotide repeats in Aspergillus nidulans. As previously found, the probability of polymorphism increased with increasing number of repeating units. Dinucleotide and trinucleotide repeats had higher probabilities of polymorphism than mononucleotide repeats, but this was offset by the presence of numerous long mononucleotide repeats within the genome. Mononucleotide microsatellites with 20 or more repeating units have a probability of polymorphism similar to dinucleotide and trinucleotide microsatellites, and therefore, consideration of mononucleotide repeats will substantially increase the number of potential markers available.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".