Molecular marker development and genetic diversity exploration by RNA-seq in <i>Platycodon grandiflorum</i>
Bibliographic record
Abstract
Platycodon grandiflorum, generally known as the bellflower or balloon flower, is the only species in the genus Platycodon of the family Campanulaceae. Platycodon plants have been traditionally used as a medicinal crop in East Asia for their antiphlogistic, antitussive, and expectorant properties. Despite these practical uses, marker-assisted selection and molecular breeding in platycodons have lagged due to the lack of genetic information on this genus. In this study, we performed RNA-seq analysis of three platycodon accessions to develop molecular markers and explore genetic diversity. First, genic simple sequence repeats (SSRs) were retrieved and compared; dinucleotide motifs were the most abundant repeats (39%-40%) followed by trinucleotide (25%-31%), tetranucleotide (1.5%-1.9%), and pentanucleotide (0.3%-1.0%) repeats. The result of in silico SSR analysis, three SSR markers were detected and showed possibility to distinguish three platycodon accessions. After several filtering procedures, 180 single nucleotide polymorphisms (SNPs) were used to design 40 cleaved amplified polymorphic sequence (CAPS) markers. Twelve of these PCR-based markers were validated as highly polymorphic and utilized to investigate genetic diversity in 21 platycodon accessions collected from various regions of South Korea. Collectively, the 12 markers yielded 35 alleles, with an average of 3 alleles per locus. Polymorphism information content (PIC) values ranged from 0.087 to 0.693, averaging 0.373 per locus. Since platycodon genetics have not been actively studied, the sequence information and the DNA markers generated from our research have the potential to contribute to further genetic improvements, genomic studies, and gene discovery in this genus.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".