The pangenome enhances the understanding of the genetic diversity of papaya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Papaya (Carica papaya L.) is a nutritionally and medicinally important tropical fruit crop, yet its genetic improvement has been limited by insufficient genomic resources. In this study, we constructed chromosome-level genomes for three key varieties (Zhufeng, T3, and T5) and integrated them with three existing assemblies to build a comprehensive pangenome, including graph-based, linear, and syntelog-based representations. The syntelog-based pangenome revealed 24 453 syntelog groups (SGs). Leveraging resequencing data from 222 accessions aligned to the graph-based pangenome, we identified 26 173 structural variations (SVs), including a functionally relevant 94-bp deletion in the RETARDED ROOT GROWTH (RRG) gene in the T3 genome. This deletion affects the expression of the RRG, resulting in a reduction in its expression level in T3. Further phenotypic analysis showed that RRG can influence papaya root length by promoting the proliferation of root meristem cells and inhibiting cell elongation. Additionally, the linear pangenome uncovered 5273 translocations and 1440 inversions, significantly expanding the known SV repertoire in papaya. This study provides a critical genomic resource for deciphering domestication-related traits and accelerating marker-assisted breeding, ultimately advancing the genetic improvement of papaya.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it