Genetic variation and relationship among and within <i>Withania</i> species as revealed by AFLP markers
Bibliographic record
Abstract
Withania somnifera is an important medicinal plant, and its anticancerous properties have been attributed to various classes of withanolide compounds. The objective of the present study was to investigate the inter- and intraspecific genetic variation present in 35 individuals of W. somnifera and 5 individuals of W. coagulans using AFLP (amplified fragment length polymorphism) marker technique. The information about genetic variation determined from AFLP data for 40 individuals was employed to estimate similarity matrix value based on Jaccard's coefficient. The similarity values were further used to construct a phenetic dendrogram revealing the genetic relationships. The dendrogram generated by UPGMA (unweighted pair group method of arithmetic averages) distinguished W. somnifera from W. coagulans and formed two major clusters. These two main clusters shared a similarity coefficient of 0.3, correlating with the high level of polymorphism detected. The dendrogram further separated W. somnifera into three subclasses corresponding to Kashmiri and Nagori groups and an intermediate type. The AFLP profile of Kashmiri individuals was distinct from that of the Nagori group of plants. The intermediate genotype was distinct as it shared bands with both the Kashmiri and Nagori individuals, even though it was identified as a Kashmiri morphotype. Furthermore, the intermediate type shared a similarity coefficient of 0.8 with the Kashmiri individuals. The present work revealed low levels of variation within a population though high levels of polymorphism were detected between Nagori and Kashmiri populations. The ability of AFLP markers for efficient and rapid detection of genetic variations at the species as well as intraspecific level qualifies it as an efficient tool for estimating genetic similarity in plant species and effective management of genetic resources.
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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".