Genotyping-by-Sequencing Enhances Genetic Diversity Analysis of Crested Wheatgrass [Agropyron cristatum (L.) Gaertn.]
Bibliographic record
Abstract
Molecular characterization of unsequenced plant species with complex genomes is now possible by genotyping-by-sequencing (GBS) using recent next generation sequencing technologies. This study represents the first use of GBS application to sample genome-wide variants of crested wheatgrass [Agropyron cristatum (L.) Gaertn.] and assess the genetic diversity present in 192 genotypes from 12 tetraploid lines. Bioinformatic analysis identified 45,507 single nucleotide polymorphism (SNP) markers in this outcrossing grass species. The model-based Bayesian analysis revealed four major clusters of the samples assayed. The diversity analysis revealed 15.8% of SNP variation residing among the 12 lines, and 12.1% SNP variation present among four genetic clusters identified by the Bayesian analysis. The principal coordinates analysis and dendrogram were able to distinguish four lines of Asian origin from Canadian cultivars and breeding lines. These results serve as a valuable resource for understanding genetic variability, and will aid in the genetic improvement of this outcrossing polyploid grass species for forage production. These findings illustrate the potential of GBS application in the characterization of non-model polyploid plants with complex genomes.
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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) | 0.001 | 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".