Development and Characterization of Microsatellite Markers for a Little Bluestem Collection
Bibliographic record
Abstract
Little bluestem ( Schizachyrium scoparium ) is a perennial bunchgrass that is native to North American prairies and woodlands from southern Canada to northern Mexico. Originally used as a forage grass, little bluestem is now listed as a major U.S. native, ornamental grass. With the widespread planting of only a few cultivars, we aimed to assess the ploidy level and genetic diversity among some popular cultivars and accessions in the U.S. Department of Agriculture National Plant Germplasm System collection. Ten microsatellite markers, with successful amplification, were developed by using sequences available in Genbank and additional simple sequence repeat (SSR) markers were generated by using ion torrent sequencing of a genomic library created from the cultivar The Blues. A total of 2812 primer sets was designed from high-throughput sequencing, 100 primer pairs were selected, and 82 of these primers successfully amplified DNA from the Schizachyrium accessions. Only 35 primer pairs, generating 102 scored fragments, were polymorphic among S. scoparium accessions. Twenty-two primer pairs generated more than four fragments per accession. The use of a repetitive sequence identifier found that of 117 examined sequences, only nine sequences did not have similarity to DNA transposons, retrotransposons, viruses, or satellite sequences. The most frequently identified fragments were the long terminal repeat retrotransposons Gypsy (177 fragments) and Copia (98 fragments) and the DNA transposon EnSpm (60 fragments). Using the software program Structure, cluster analysis of the SSR data for S. scoparium revealed four groups. The lowest genetic similarity between little bluestem samples was 86%, which was surprising as a high degree of morphological variation is seen in this species. Furthermore, no variation in ploidy level was seen among little bluestem samples. These microsatellite markers are the first sequence-specific markers designed for little bluestem and can serve as a resource for future genetic studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".