Genotyping and Genetic Diversity Analysis of 47 Flowering Cherry (<I>Cerasus</i>) Germplasms
Bibliographic record
Abstract
In order to provide a theoretical basis for conservation and utilization of excellent flowering cherry germplasms, genetic diversity and genotype were analyzed based on single nucleotide polymorphism (SNP) molecular markers. A total of 47 germplasms were sequenced using restriction site-associated DNA sequencing (RAD-Seq) method, and highly consistent SNP sites have been identified for genetic diversity analysis and genotyping. The RAxML program was used for phylogenetic tree construction, based on the maximum likelihood (ML) method. The ADMIXTURE software was used to analyze genetic structure. The GCTA software was used for principal component analysis. Genetic diversity parameters, includes nucleotide diversity (π value), expected heterozygosity (exp He ) and genetic differentiation index ( F ST ), were carried out using the PopGenome and Arlequin 3.0 software. A total of 79 667 highly consistent SNPs were obtained, after genotype integrity filtering and closely linked sites screening. According to the phylogenetic, principal components and population structure analysis results, the 47 germplasms could be divided into eight genetic clusters. The π and exp He value of each cluster was as follows: I: 0.128 19, 0.119 94; II: 0.139 64, 0.130 55; III: 0.21 55, 0.164 73; IV: 0.086 82, 0.061 22; V: 0.095 49, 0.069 73; VI: 0.191 22, 0.10 61; VII: 0.16 85, 0.158 78; VIII: 0.290 98, 0.183 43. The cluster IV and V presented the largest genetic differentiation, with an F ST value of 0.4612 89, followed by IV and VI, with an F ST value of 0.456 958; the lowest genetic differentiation existed between the cluster VII and VIII, with an F ST value of 0.0976 13. Except for cluster VII and VIII, the genetic differentiation among the other clusters was at or above the medium level. The results of genotyping showed that there were 29 individuals (61.70 %) with single genetic component, and 18 individuals (38.30 %) with two or three genetic components. Based on the results of genetic components analysis, there were four potential interspecific hybridizations. There was a high genetic diversity among 47 flowering cherry germplasms, obvious genetic differentiation among the eight clusters. The genetic components of natural hybrid individuals and artificial hybrid cultivars were revealed, and their parents were inferred, based on the genotyping results.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".