Frequent numerical and structural chromosome changes in early generations of synthetic hexaploid wheat
Bibliographic record
Abstract
Modern hexaploid wheat (Triticum aestivum L.; AABBDD) has evolved from a hybrid of tetraploid wheat (closely related to Triticum turgidum L. ssp. durum (Desf.) Husn., AABB) and goatgrass (Aegilops tauschii Coss., DD). Variations in chromosome structure and ploidy have played important roles in wheat evolution. How these variations occur and their role in expanding the genetic diversity of modern wheat remain largely unknown. Synthetic hexaploid wheat (SHW) can be used to investigate chromosome variations that occur during the early generations of existence. SHW lines derived by crossing durum wheat ‘Langdon’ with 12 Ae. tauschii accessions were analyzed using oligonucleotide probe multiplex fluorescence in situ hybridization (FISH) of metaphase chromosomes and SNP markers. Cluster analysis based on SNP markers categorizes them into three groups. Among 702 plants from the S8 and S9 generations, 415 (59.12%) carried chromosome variations involving all 21 chromosomes, but with different frequencies for each chromosome and sub-genome. Total chromosome variation frequencies varied between lines, but there was no significant difference among the three groups. The non-random chromosome variations in the SHW lines detected in this study may indicate that similar variations occurred in the early stages of wheat polyploidization and played important roles in wheat evolution.
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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) | 0.001 | 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".