Rapid development of PCR-based genome-specific repetitive DNA junction markers in wheat
Bibliographic record
Abstract
In hexaploid wheat (Triticum aestivum L.) (AABBDD, C=17 000 Mb), repeat DNA accounts for approximately 90% of the genome, of which transposable elements (TEs) constitute 60%-80%. Despite the dynamic evolution of TEs, our previous study indicated that the majority of TEs are conserved and collinear between the homologous wheat genomes, based on identical insertion patterns. In this study, we exploited the unique and abundant TE insertion junction regions identified from diploid Aegilops tauschii to develop genome-specific repeat DNA junction markers (RJM) for use in hexaploid wheat. In this study, both BAC end and random shotgun sequences were used to search for RJM. Of the 300 RJM primer pairs tested, 269 (90%) amplified single bands from diploid Ae. tauschii. Of these 269 primer pairs, 260 (97%) amplified hexaploid wheat and 9 (3%) amplified Ae. tauschii only. Among the RJM primers that amplified hexaploid wheat, 88% were successfully assigned to individual chromosomes of the hexaploid D genome. Among the 38 RJM primers mapped on chromosome 6D, 31 (82%) were unambiguously mapped to delineated bins of the chromosome using various wheat deletion lines. Our results suggest that the unique RJM derived from the diploid D genome could facilitate genetic, physical, and radiation mapping of the hexaploid wheat D genome.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".