Cytogenetic and molecular markers for detecting <i>Aegilops uniaristata</i> chromosomes in a wheat background
Bibliographic record
Abstract
Aegilops uniaristata has many agronomically useful traits that can be used for wheat breeding. So far, a Triticum turgidum - Ae. uniaristata amphiploid and one set of Chinese Spring (CS) - Ae. uniaristata addition lines have been produced. To guide Ae. uniaristata chromatin transformation from these lines into cultivated wheat through chromosome engineering, reliable cytogenetic and molecular markers specific for Ae. uniaristata chromosomes need to be developed. Standard C-banding shows that C-bands mainly exist in the centromeric regions of Ae. uniaristata but rarely at the distal ends. Fluorescence in situ hybridization (FISH) using (GAA)8 as a probe showed that the hybridization signal of chromosomes 1N-7N are different, thus (GAA)8 can be used to identify all Ae. uniaristata chromosomes in wheat background simultaneously. Moreover, a total of 42 molecular markers specific for Ae. uniaristata chromosomes were developed by screening expressed sequence tag - sequence tagged site (EST-STS), expressed sequence tag - simple sequence repeat (EST-SSR), and PCR-based landmark unique gene (PLUG) primers. The markers were subsequently localized using the CS - Ae. uniaristata addition lines and different wheat cultivars as controls. The cytogenetic and molecular markers developed herein will be helpful for screening and identifying wheat - Ae. uniaristata progeny.
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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 | 0.001 | 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 | 0.001 |
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".