Effect of quantitative trait loci for seed shattering on abscission layer formation in Asian wild rice <i>Oryza rufipogon</i>
Bibliographic record
Abstract
Asian cultivated rice Oryza sativa L. was domesticated from its wild ancestor, O. rufipogon. During domestication, the cultivated rice lost its seed-shattering behaviour. Previous studies have shown that two major quantitative trait loci (QTLs; qSH1 and sh4) are responsible for the seed-shattering degree. Here, we produced introgression lines carrying non-functional alleles from O. sativa 'Nipponbare' at the two major QTLs in the genetic background of wild rice O. rufipogon W630, and examined the effects of the two QTLs on seed shattering and abscission layer formation. The introgression lines, with Nipponbare alleles at either or both loci, showed complete or partial abscission layer formation, respectively, indicating that other unknown loci might be involved in enhancing seed shattering in wild rice. We detected a single QTL named qSH3 regulating seed-shattering degree using an F2 population between Nipponbare and the introgression line carrying Nipponbare alleles at the two QTLs. Although we generated an introgression line for qSH3 alone, no effects on seed shattering were observed. However, a significant effect on seed-shattering degree was observed for the introgression line carrying Nipponbare alleles at qSH3 and the two QTLs, suggesting an important role of qSH3 on seed shattering in coordination with the two QTLs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".