Nuclear- and chloroplast-microsatellite variation in A-genome species of rice
Bibliographic record
Abstract
Simple sequence length polymorphism analysis was carried out to reveal microsatellite variation and to clarify the phylogenetic relationships among A-genome species of rice. Total DNA from 29 cultivars (23 Oryza sativa and 6 O. glaberrima) and 30 accessions of wild A-genome species (12 O. rufipogon, 5 O. glumaepatula, 2 O. longistaminata, 6 O. meridionalis, and 5 O. barthii) was used as a template for PCR to detect 24 nuclear and 10 chloroplast microsatellite loci. Microsatellite allelic diversity was examined based on amplified banding patterns. Microsatellites amplified clearly in all 59 accessions, with an average of 18.4 alleles per locus. The polymorphism information content (PIC) value ranged from 0.85 to 0.94, with an average of 0.89. At the species level, high average PIC values were observed in O. sativa (0.79) and O. rufipogon (0.80). For chloroplast microsatellites, the average number of alleles per locus and the average PIC value were 2.9 and 0.38, respectively. While the magnitude of diversity was much greater for nuclear microsatellites than for chloroplast microsatellites, they showed parallel patterns of differentiation for each taxonomic group. Using the ratio of common alleles (estimated as size of amplified fragments) as a similarity index, the average percentages of common microsatellite alleles were calculated between taxa. For both nuclear and chloroplast microsatellites, O. sativa showed the highest similarity values to O. rufipogon, and O. glaberrima was most similar to O. barthii. These data support previous evidence that these cultivars originated from the corresponding wild ancestral species.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".