Overexpression of OsSPL14 results in transcriptome and physiology changes in indica rice ‘MH86’
Bibliographic record
Abstract
Abstract Oryza sativa SPL14 (OsSPL14), identified as the IDEAL PLANT ARCHITECTURE1 or WEALTHY FARMER’S PANICLE gene, plays a critical role in regulating rice plant architecture. Here, OsSPL14-overexpression transgenic rice plants had shorter growth periods, short narrow flag leaves, and thick green leaves compared with wild type ‘MH86’ plants (WT). Additionally, transgenic lines had higher chlorophyll a (Chl a), chlorophyll b (Chl b), and carotenoid (Car x) contents at both seedling and mature stages. Expression of OsSPL14 increased at transcriptional level, and OsSPL14 protein level was substantially increased in transgenic lines relative to WT. A transcriptome analysis identified 473 up-regulated and 103 down-regulated genes in the transgenic plants. The expression of differentially expressed genes (DEGs) involved in carotenoid biosynthesis, abscisic acid (ABA) metabolism, and lignin biosynthesis increased significantly. Most of DEGs participated in “plant hormone signal transduction” and “starch and sucrose metabolism” were also up-regulated in the transgenic plants. In addition, there were higher ABA and gibberellin acid 3 (GA3) levels in OsSPL14-overexpression rice plants at seedling and tillering stages compared with WT. In contrast with that of WT, lignin and cellulose contents of culm increased distinctly. Also, silicon and potassium contents increased dramatically in transgenic lines. Meanwhile, the chalkiness ratios and chalkiness degrees decreased, and the gel consistency levels improved in transgenic lines. Thus, overexpression of OsSPL14 influenced growth period, leaf development, hormonal levels, culm composition, and grain quality characters of rice, which provides more insight into the function of OsSPL14.
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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 | 0.000 | 0.000 |
| 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".