Genetic Diversity, Population Structure, and Botanical Variety of 320 Global Peanut Accessions Revealed Through Tunable Genotyping-by-Sequencing
Bibliographic record
Abstract
Abstract Cultivated peanut (Arachis hypogaeaL.) were classified into six botanical varieties according to the morphological characteristics. However, their genetic evolutionary relationships at the genome-wide level were still unclear. A total of 320 peanut accessions, including four of the six botanical varieties, and 37,128 high-quality single nucleotide polymorphisms (SNPs) detected by tunable genotyping-by-sequencing (tGBS) were used to reveal the evolutionary relationships among different botanical varieties and verify the phenotypic classification. A phylogenetic tree indicated that the tested accessions were grouped into three clusters. Almost all of the peanut accessions in cluster C1 belong to var.fastigiata, and clusters C2 and C3 mainly consisted of accessions from var.vulgarisand subsp.hypogaea, respectively. The results of a principal component analysis were consistent with relationships revealed in the phylogenetic tree. Population structure analysis showed that var.fastigiataand var.vulgariswere not separated when K = 2 (subgroup number), whereas they were clearly divided when K = 3. However, var.hypogaeaand var.hirsutacould not be distinguished from each other all the way. The nucleotide diversity (π) value implied that var.vulgarisexhibited the highest genetic diversity (0.048), followed by var.fastigiata(0.035) and subsp.hypogaea(0.012), which is consistent with the result of phylogenetic tree. Moreover, the fixation index (FST) value confirmed that var.fastigiataand var.vulgariswere closely related to each other (FST = 0.284), while both of them were clearly distinct from var.hypogaea(FST > 0.4). The present study confirmed the traditional botanical classifications of cultivated peanut at the genome-wide level. Furthermore, the reliable SNPs identified in this study may be a valuable resource for peanut breeders.
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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 | 0.001 | 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".