Population Dynamics Among six Major Groups of the Oryza rufipogon Species Complex, Wild Relative of Cultivated Asian Rice
Bibliographic record
Abstract
Understanding population structure of the wild progenitor of Asian cultivated rice (O. sativa), the Oryza rufipogon species complex (ORSC), is of interest to plant breeders and contributes to our understanding of rice domestication. A collection of 286 diverse ORSC accessions was evaluated for nuclear variation using genotyping-by-sequencing (113,739 SNPs) and for chloroplast variation using Sanger sequencing (25 polymorphic sites). Six wild subpopulations were identified, with 25 % of accessions classified as admixed. Three of the wild groups were genetically and geographically closely related to the O. sativa subpopulations, indica, aus and japonica, and carried O. sativa introgressions; the other three wild groups were genetically divergent, had unique chloroplast haplotypes, and were located at the geographical extremes of the species range. The genetic subpopulations were significantly correlated (r 2 = 0.562) with traditional species designations, O. rufipogon (perennial) and O. nivara (annual), differentiated based on morphology and life history. A wild diversity panel of 95 purified (inbred) accessions was developed for future genetic studies. Our results suggest that the cultivated aus subpopulation is most closely related to an annual wild relative, japonica to a perennial wild relative, and indica to an admixed population of diverse annual and perennial wild ancestors. Gene flow between ORSC and O. sativa is common in regions where rice is cultivated, threatening the identity and diversity of wild ORSC populations. The three geographically isolated ORSC populations harbor variation rarely seen in cultivated rice and provide a unique window into the genetic composition of ancient rice subpopulations.
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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 | 0.001 | 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) | 0.000 | 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".