Genetic variability and phytogeography of<i>Miscanthus sinensis</i>var.<i>condensatus</i>, an apomictic grass, based on RAPD fingerprints
Bibliographic record
Abstract
DNA fingerprinting using random amplified polymorphic DNA (RAPD) markers was employed to investigate the genetic variation within and among populations of Miscanthus Anderss. sinensis var. condensatus (Hack.) Makino, an apomictic grass distributed along the coasts of Taiwan and Ryukyu Islands. A total of 250 plants from three Taiwanese populations (Southeast Coast, Orchid Islet, and Green Islet) and two populations from Ryukyu (Ishigaki and Amami-O-Shima Islets) were sampled. The amplified products of 40 random primers showed monomorphic banding patterns within all populations as well as among the three populations from Taiwan. Low genetic variation (with only two polymorphic loci), but significant differentiation, was detected between populations from Taiwan and Ryukyu (ΦCT= 0.864) and between populations (ΦST= 1.0) from Ishigaki and Amami-O-Shima Islets. In contrast, a high level of variation was exhibited in the outcrossing Miscanthus sinensis var. glaber (Nakai) Li. In addition to apomictic reproduction, low genetic variation across populations of M. sinensis var. condensatus may be a result of high salinity acting as a selective agent. With the cost of reduced genetic heterogeneity, apomixis may have provided a mechanism for avoiding the transmission of endophytic fungi. The phytogeographic pattern of M. sinensis var. condensatus, as reflected by the RAPD data, likely represents isolation between Taiwan and Ryukyu since the mid-Pleistocene.Key words: apomixis, Miscanthus sinensis var. condensatus, phytogeography, population differentiation, RAPD, system of mating.
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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".