Microsatellite DNA Analysis of Genetic Diversity and Parentage Testing in the Popular Dog Breeds in Poland
Bibliographic record
Abstract
There is growing concern that extreme breed standardization contributes to a reduction of the effective population size and high levels of inbreeding, resulting in the loss of genetic diversity in many breeds. This study examined genetic diversity among eight popular dog breeds in Poland and evaluated the effectiveness of a 21-microsatellite (STR) panel recommended by the International Society for Animal Genetics (ISAG) for parent verification. The following breeds were characterized: German Shepherd, Maltese, Irish Wolfhound, Yorkshire Terrier, Biewer Yorkshire Terrier, Golden Retriever, Labrador Retriever, and French Bulldog. STRUCTURE analysis showed breed distinctiveness among all the dog breeds under study. Reynold’s distance ranged between θw = 0.634 and θw = 0.260. The studied breeds showed a medium level of genetic differentiation; the mean number of alleles per locus ranged from 3.4 to 6.6, and the effective number of alleles from 2.1 to 3.5. The mean degree of heterozygosity varied from 49% to 69% and from 47% to 68% for HO and HE, respectively. The population inbreeding coefficient (FIS) indicated an absence of inbreeding in the studied breeds. The average polymorphism information content (PIC) values for most of the breeds were higher than 0.5. The cumulative power of discrimination (PD) for all the markers in all breeds reached high values (close to 1.0), while the probability of identity (PID) was low, ranging between 10−11 and 10−19. The cumulative exclusion probability when the genotypes of one (PE1) and both parents (PE2) are known and showed that the parentage can be confirmed with a probability of 94.92% to 99.95% and 99.78% to 99.9999%, respectively.
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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".