Cross Species Amplification of Adzukibean Derived Microsatellite Loci and Diversity Analysis in Greengram and Related <i>Vigna</i> Species
Bibliographic record
Abstract
Greengram or mungbean ( Vigna radiata (L.) Wilczek) is a well known grain legume in Asian countries. Among the different DNA markers, microsatellite or simple sequence repeats (SSRs) are the markers of choice for various genetic studies due to co-dominant nature, loci specificity and high reproducibility. In the present study, a set of thirty-five microsatellite primer pairs derived from adzukibean ( Vigna angularis (Willd.) Ohwi & Ohashi) were used to assess the transferability and tested for their ability to amplify microsatellite loci in greengram and related Vigna species. Of the thirty five microsatellite markers, thirty-two were successfully amplified across the thirty six genotypes and twenty eight were polymorphic. A total of 83 microsatellite alleles were generated with an average of 2.96 alleles per locus. Number of alleles ranged from two to five. Dendrogram formed based on UPGMA, 36 genotypes were grouped into five clusters. Similarly, the neighbour-joining tree developed based on weighted average for dissimilarity matrix grouped 36 genotypes into five groups. The finding suggests that adzukibean derived microsatellite markers are highly informative and could be used to improve the greengram at molecular level.
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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 | 0.001 |
| 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".