EST-PCR, EST-SSR and ISSR markers to identify a set of wild cranberries and evaluate their relationships
Bibliographic record
Abstract
An, D., Bykova, N. V. and Debnath, S. C. 2015. EST-PCR, EST-SSR and ISSR markers to identify a set of wild cranberries and evaluate their relationships. Can. J. Plant Sci. 95: 1155-1165. The cranberry (Vaccinium marcrocarpon Ait.) is a woody, evergreen, perennial vine with great potential for economic and health benefits. Selection and use of genetically diverse genotypes are key factors in any crop breeding program to develop cultivars with a broad genetic base. Molecular markers play a major role in selecting diverse genotypes. One hundred and two wild cranberry clones collected from four Canadian provinces and five cultivars were screened with inter simple sequence repeat (ISSR), expressed sequence tag-simple sequence repeat (EST-SSR) and EST-polymerase chain reaction (PCR) markers to validate the genetic diversity and relationships among them. EST-PCRs (0.54) and EST-SSRs (0.35) generated higher frequency of major alleles than ISSRs (0.08), but ISSRs presented a higher level of polymorphism and greater polymorphic information content and expected heterozygosity than EST-SSRs and EST-PCRs. Combined cluster analysis by the unweighted pair-group method with arithmetic averages (UPGMA) separated the wild clones and cultivars into four main clusters, which was in agreement with the principal coordinate (PCo) analysis. Analysis of molecular variation detected sufficient variations among genotypes within communities and among communities within provinces with ISSR (66 and 36%, respectively), EST-PCR (72 and 34%, respectively) and EST-SSR (72 and 34%, respectively) markers. These values were 71 and 35%, respectively, for combined analysis. Combined use of three types of molecular markers, for the first time in Vaccinium species, detected a sufficient degree of variation among cranberry genotypes, allowing for differentiation and rendering these technologies valuable for genotype identification in a diverse cranberry germplasm and for more efficient parental choice in the current cranberry breeding program.
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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 | 0.001 | 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".