Development of high transferability cp<scp>SSR</scp> markers for individual identification and genetic investigation in Cupressaceae species
Bibliographic record
Abstract
Abstract Given the low substitution rate in plastomes, the polymorphic and codominant nature of chloroplast SSRs (cpSSRs) makes them ideal markers, complementing their nuclear counterpart. In Cupressaceae, cpSSRs are mostly paternally inherited, thus, they are useful in mating systems and pollen flow studies. Using e‐PCR, 92 SSR loci were identified across six Cupressaceae plastomes, and primers were designed for 26 loci with potential interspecific transferability. The 26 developed cpSSRs were polymorphic in four genera, Platycladus, Sabina, Juniperus, and Cupressus and are suitable for Cupressaceae molecular genetic studies and utilization. We genotyped 192 Platycladus orientalis samples from a core breeding population using 10 of the developed cpSSRs and 10 nuclear SSRs, and these individuals were identified with high confidence. The developed cpSSRs can be used in (1) a marker‐assisted breeding scheme, specifically when paternity identification is required, (2) population genetics investigations, and (3) biogeography of Cupressaceae and unraveling the genetic relationships between related species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".