Linkage Drag and Domestication Syndrome: The Genetic Lessons from Rice Evolution
Bibliographic record
Abstract
The domestication of rice ( Oryza sativa ) from its wild relatives has been a pivotal event in agricultural history, leading to significant genetic changes known as domestication syndrome. This study synthesizes current knowledge on the genetic mechanisms underlying these changes, with a focus on linkage drag and its implications for rice breeding. The severe bottleneck during domestication resulted in a dramatic reduction in genetic diversity in cultivated rice compared to its wild progenitors, O. rufipogon and O. nivara . Multiple independent domestication events have been identified, contributing to the genetic differentiation between the indica and japonica subspeicies. The identification of quantitative trait loci (QTLs) and candidate genes associated with domestication-related traits has provided insights into the clustered distribution of these genes, which may explain the phenomenon of linkage drag. Furthermore, the study of de-domestication in weedy rice has revealed the complexity of genetic changes during the domestication process. This study highlights the importance of understanding the genetic basis of domestication syndrome and linkage drag to improve rice breeding strategies and harness the genetic potential of wild rice species for crop improvement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".