Comprehensive Analysis of the SBP Family in Blueberry and Their Regulatory Mechanism Controlling Chlorophyll Accumulation
Bibliographic record
Abstract
SQUAMOSA Promoter Binding Protein (SBP) family genes act as central players to regulate plant growth and development with functional redundancy and specificity. Addressing the diversity of the SBP family in crops is of great significance to precisely utilize them to improve agronomic traits. Blueberry is an important economic berry crop. However, the SBP family has not been described in blueberry. In the present study, twenty VcSBP genes were identified through data mining against blueberry transcriptome databases. These VcSBPs could be clustered into eight groups, and the gene structures and motif compositions are divergent among the groups and similar within each group. The VcSBPs were differentially expressed in various tissues. Intriguingly, 10 VcSBPs were highly expressed at green fruit stages and dramatically decreased at the onset of fruit ripening, implying that they are important regulators during early fruit development. Computational analysis showed that 10 VcSBPs were targeted by miR156, and four of them were further verified by degradome sequencing. Moreover, their functional diversity was studied in Arabidopsis. Noticeably, three VcSBPs significantly increased chlorophyll accumulation, and qRT-PCR analysis indicated that VcSBP13a in Arabidopsis enhanced the expression of chlorophyll biosynthetic genes such as AtDVR, AtPORA, AtPORB, AtPORC, and AtCAO. Finally, the targets of VcSBPs were computationally identified in blueberry, and the Y1H assay showed that VcSBP13a could physically bind to the promoter region of the chlorophyll-associated gene VcLHCB1. Our findings provided an overall framework for individually understanding the characteristics and functions of the SBP family in blueberry.
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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".