Characterization of microsatellites in wild and sweet cherry (<i>Prunus avium</i> L.) markers for individual identification and reproductive processes
Bibliographic record
Abstract
Nuclear microsatellites were characterized in Prunus avium and validated as markers for individual and cultivar identification, as well as for studies of pollen- and seed-mediated gene flow. We used 20 primer pairs from a simple sequence repeat (SSR) library of Prunus persica and identified 7 loci harboring polymorphic microsatellite sequences in P. avium. In a natural population of 75 wild cherry trees, the number of alleles per locus ranged from 4 to 9 and expected heterozygosity from 0.39 to 0.77. The variability of the SSR markers allowed an unambiguous identification of individual trees and potential root suckers. Additionally, we analyzed 13 sweet cherry cultivars and differentiated 12 of them. An exclusion probability of 0.984 was calculated, which indicates that the seven loci are suitable markers for paternity analysis. The woody endocarp was successfully used for resolution of all microsatellite loci and exhibited the same multilocus genotype as the mother tree, as shown in a single seed progeny. Hence, SSR fingerprinting of the purely maternal endocarp was also successful in this Prunus species, allowing the identification of the mother tree of the dispersed seeds. The linkage of microsatellite loci with PCR-amplified alleles of the self-incompatibility locus was tested in two full-sib families of sweet cherry cultivars. From low recombination frequencies, we inferred that two loci are linked with the S locus. The present study provides markers that will significantly facilitate studies of spatial genetic variation and gene flow in wild cherry, as well as breeding programs in sweet cherry.
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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 | 0.000 |
| 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 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".