Double repression of soluble starch synthase genes <i>SSIIa</i> and <i>SSIIIa</i> in rice (<i>Oryza sativa</i> L.) uncovers interactive effects on the physicochemical properties of starch
Bibliographic record
Abstract
Soluble starch synthases (SSs) are major enzymes involved in starch biosynthesis in developing rice (Oryza sativa L.) endosperm. Despite extensive studies of SSs in various plant species including rice, the functional modes of action among multiple SS genes are still not clear. Here, we generated transgenic RNA interference (RNAi) repressed lines for seven of the eight members of the rice SS gene family and studied their effects on starch synthesis and grain formation. Consistent with their expression domains, RNAi repression of genes that encode isozymes SSI, SSIIa, and SSIIIa had strong effects on grain development, whereas no obvious phenotypic changes were observed in transgenic plants with the other SS genes being RNAi repressed, indicating functional redundancies among the genes. To study the potential functional interactions of SS genes, we generated SSIIa/SSIIIa double repression lines whose kernels displayed a chalky kernel appearance and had increased amylose levels, increased pasting temperatures, and decreased viscosities. The double mutation also reduced short (degree of polymerization (DP) 5-6) and long (DP 12-23) amylopectin chain contents in the grain and increased the medium long types (DP 7-11). The nonadditive nature of the double mutation line suggests that SSIIa and SSIIIa interact with each other during starch synthesis. Such interaction may be physical via starch phophorylase as indicated by our pair-wise yeast two-hybrid assays on major starch synthesis enzymes. Collectively, the data showed that SSIIa and SSIIIa play distinctive, but partially overlapping, roles during rice grain starch synthesis. The possibility of extensive redundancy or complementarity among SS isozymes is discussed.
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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) | 0.001 | 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 | 0.001 |
| 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".