Generation of amphidiploids from hybrids of wheat and related species from the genera <i>Aegilops</i>, <i>Secale</i>, <i>Thinopyrum</i>, and <i>Triticum</i> as a source of genetic variation for wheat improvement
Bibliographic record
Abstract
We aim to improve diversity of domesticated wheat by transferring genetic variation for important target traits from related wild and cultivated grass species. The present study describes the development of F1 hybrids between wheat and related species from the genera Aegilops, Secale, Thinopyrum, and Triticum and production of new amphidiploids. Amphidiploid lines were produced from 20 different distant relatives. Both colchicine and caffeine were successfully used to double the chromosome numbers. The genomic constitution of the newly formed amphidiploids derived from seven distant relatives was determined using genomic in situ hybridization (GISH). Altogether, 42 different plants were analysed, 19 using multicolour GISH separating the chromosomes from the A, B, and D genomes of wheat, as well as the distant relative, and 23 using single colour GISH. Restructuring of the allopolyploid genome, both chromosome losses and aneuploidy, was detected in all the genomes contained by the amphidiploids. From the observed chromosome numbers there is an indication that in amphidiploids the B genome of wheat suffers chromosome losses less frequently than the other wheat genomes. Phenotyping to realize the full potential of the wheat-related grass germplasm is underway, linking the analyzed genotypes to agronomically important target traits.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".