Development of a Large Gene-Associated SSR Marker Set and in-Depth Genetic Characterization in Scarlet Sage
Bibliographic record
Abstract
Salvia splendens, scarlet or tropical sage, is a tender perennial herbaceous flowering plant popularly grown in public and private gardens all over the world. In this study, we developed a set of simple sequence repeats (SSRs) from genome-wide sequences to assess the genetic diversity and population structure among 112 cultivars. We obtained 364,379 SSR markers by mining scarlet sage’s recently published whole genome sequence; 14,545 genic SSR loci were identified in 2 kb gene flanking regions. Among the 768 genic SSR primer sets we screened, 576 loci successfully amplified in DNA pools of 3-4 different cultivars, of which 271 remained polymorphic when tested across eight individual plants. We searched for the related gene functions attributable to these genic SSRs using diverse databases, resulting in 259 Non-redundant matching sequences, 205 individual Gene Ontology terms, 236 assigned to eukaryotic orthologous groups, and 67 KEGG-annotated (Kyoto Encyclopedia of Genes and Genomes) sequences. We finally selected 41 polymorphic SSR loci to infer genetic diversity and population structure among 112 S. splendens accessions. Based on genic-SSR markers, clustering analyses consistently revealed two distinct genetic groups within the core collection. This work developed and characterized an exhaustive set of genome-wide genic SSR markers for scarlet sage. These SSRs can provide species identification, genetic diversity and population structure information for S. splendens, and will therefore be important tools for the management and protection of S. splendens germplasm.
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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".