Genome-wide identification of the peach LOB/LBD genes and the positive role of the PpNAP4–PpLOB1 module in peach fruit softening
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
PpLOB1 positively regulates peach softening. PpNAP4 activates PpLOB1 expression. Softening of fleshy fruits during ripening and post-harvest is a programmed event that greatly affects quality and storage span. However, the molecular mechanism underlying peach softening remain largely unknown. Lateral organ boundary (LOB) domain (LBD) proteins are pivotal regulators of plant growth and development. To date, certain LOB/LBD transcription factors are seemingly implicated in fruit softening. In this study, we identified 42 LOB/LBD genes in the peach genome. Expression analysis showed a significant upregulation of PpLOB1 transcripts toward peach fruit ripening. PpLOB1 was classified into Class II subgroup, and showed high sequence similarity to several softening-related LOB/LBD transcription factors. Transient transformation assays showed that PpLOB1 positively modulates peach softening. Further experiments demonstrated that PpLOB1 directly targeted and activated the promoters of pectate lyase 1 ( PpPL1 ) and PpPL15 , thereby contributing to the regulation of fruit softening. Additionally, PpNAP4 up-regulated PpLOB1 expression by binding to its promoter. Meanwhile, our findings revealed that PpNAP4 and PpNAP6 cooperatively modulate the expression of PpLOB1 . Altogether, all results revealed a new regulatory module that involves PpNAP4 and PpLOB1, and contributes to peach fruit softening.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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