Characterization of AFLP markers in damselflies: prevalence of codominant markers and implications for population genetic applications
Bibliographic record
Abstract
Amplified fragment length polymorphism (AFLP) analysis is becoming increasingly popular as a method for generating molecular markers for population genetic applications. For practical considerations, it is generally assumed in population studies that AFLPs segregate as dominant markers, i.e., that present and absent are the only possible states of a given locus. We tested the assumption of dominance in natural populations of the damselfly Nehalennia irene (Hagen) (Odonata: Coenagrionidae). Electro-blotted AFLP products from 21 samples were probed with individual markers. Eleven markers were analyzed, of which two were monomorphic and nine were polymorphic. Only two of the polymorphic markers behaved in a strictly dominant manner. The remaining seven polymorphic markers displayed various degrees of codominance, with 2-10 visible alleles in the sample. Of the three markers displaying the highest degree of variability, two contained microsatellite repeat tracts. Our results suggest that the assumption of dominance is unfounded. As a result, AFLP analysis may be unsuitable for estimating several important population genetic parameters, including genetic diversity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".