Peach chloroplast genome variation architecture and phylogenomic signatures of cpDNA introgression in <i>Prunus</i>
Bibliographic record
Abstract
The complete chloroplast genome of peach provides essential information required for the assessment of phylogenetic relationships among Prunus species. Here, we compared the complete chloroplast DNA (cpDNA) genome between two peach cultivars and a wild relative, Prunus mira. The cpDNA genomes of the three peach specimens ranged from 157 330 to 157 744 bp in length and all contained 133 genes and 128 intergenic spacer (IGS) regions with an average GC content of 36.8%. The cpDNA genome of peach contained approximately 600 simple sequence repeats (SSRs), with hexa-nucleotide repeats being the most frequent microsatellites. Most SSRs have undergone divergence between cultivated and wild peaches. A total of 331 single nucleotide variants were identified in the cpDNA genomes. Fifty-one multiple-base pair indels were detected, which are mainly responsible for the cpDNA genome size variation. The cpDNA genomes contained 45 hypervariable regions, with 78% in the large single copy region (LSC). Phylogenomic analysis revealed that Prunus persica is more closely related to Prunus kansuensis than to other wild relatives, and a frequency of introgression of the chloroplast genome between Prunus species was deduced. Collectively, various genetic variations in the cpDNA genomes can serve as molecular markers for genomic studies of Prunus species, such as DNA barcoding, phylogeny, and systematics.
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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".