Cross-species amplification from crop soybean<i>Glycine max</i>provides informative microsatellite markers for the study of inbreeding wild relatives
Bibliographic record
Abstract
The development of microsatellite markers through transfer of primers from related species (cross-species amplification) remains a little-explored alternative to the de novo method in plants. In this study of 100 microsatellite loci from Glycine max, we examined two aspects of primer transfer. First, we tested if source locus properties can predict primer transfer and polymorphism in Glycine cyrtoloba and Glycine clandestina. We transferred 23 primers to G. cyrtoloba and 42 to G. clandestina, with 19 loci polymorphic within G. clandestina. However, we could not predict transfer or polymorphism from the source locus properties. Second, we evaluated the subset of 11 polymorphic loci for study in G. clandestina populations representing two local morphotypes. All loci were informative within populations (population mean He +/- SE = 0.58 +/- 0.04). We directly sequenced 28 alleles at 4 representative loci. The allelic patterns and sequencing results established that 8 of 11 loci were typical microsatellites, confirming the utility of primer transfer as an alternative to de novo development. Additionally, we found that morphotypic differentiation between populations was paralleled by changes in polymorphism level at six loci and size homoplasy at one locus. We interpret these patterns as being a product of selfing in G. clandestina. Our results demonstrate the value of allele sequence knowledge for the most effective use of microsatellites.
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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) | 0.001 | 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) | 0.001 | 0.001 |
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".