RAPD and ISSR fingerprints as useful genetic markers for analysis of genetic diversity, varietal identification, and phylogenetic relationships in peanut (<i>Arachis hypogaea</i>) cultivars and wild species
Bibliographic record
Abstract
Abstract: Twenty-one random and 29 SSR primers were used to assess genetic variation and interrelationships among subspecies and botanical varieties of cultivated peanut, Arachis hypogaea (2n = 4x = 40), and phylogenetic relationships among cultivated peanut and wild species of the genus Arachis. In contrast with the previous generalization that peanut accessions lack genetic variation, both random and SSR primers revealed 42.7 and 54.4% polymorphism, respectively, among 220 and 124 genetic loci amplified from 13 accessions. Moreover, the dendrograms based on RAPD, ISSR, and RAPD + ISSR data precisely organized the five botanical varieties of the two subspecies into five clusters. One SSR primer was identified that could distinguish all the accessions analysed within a variety. Although the polymorphic index content varied from 0.1 to 0.5 for both ISSR and RAPD markers, primer index values were substantially higher for RAPD primers (0.35-4.65) than for SSR primers (0.35-1.73). It was possible to identify accessions, particularly those of divergent origins, by RAPD and (or) ISSR fingerprints. Based on these results, marker-based genetic improvement in A. hypogaea appears possible. None of the 486 RAPD and 330 ISSR amplification products were found to be commonly shared among 13 species of section Arachis and one species each of sections Heteranthae, Rhizomatosae, and Procumbentes. Dendrograms constructed from RAPD, ISSR, and RAPD + ISSR data showed overall similar topologies. They could be resolved into four groups corresponding to the species grouped in four taxonomic sections. The present results strongly support the view that Arachis monticola (2n = 4x = 40) and A. hypogaea are very closely related, and indicate that A. villosa and A. ipaensis are the diploid wild progenitors of these tetraploid species.
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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 | 0.000 |
| 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".