Identifying rubber‐related genes through developing a sense/antisense RNA expression mutant library of <i>Taraxacum kok‐saghyz</i> Rodin
Bibliographic record
Abstract
Taraxacum kok-saghyz Rodin (TKS) is a promising alternative crop source for producing high-quality natural rubber (NR) and has become an ideal model plant for studying NR biosynthesis, regulation mechanisms, and production. So far, only a very limited number of functional genes related to NR biosynthesis have been identified in TKS. To achieve a systematic identification of its novel functional genes, we developed a mutant system denoted sense/antisense RNA expression (SARE) and have generated more than 8,000 transgenic TKS plants. A series of mutants with altered phenotypes, particularly changes in NR contents, were identified. To evaluate the efficiency of this library, we chose one mutant, c112, which exhibits a significant increase in NR content, for in-depth characterization. The c112 mutant arose from the sense insertion of a dormancy-associated gene1 (DRM1)/auxin repressed protein (ARP) gene, which we named high natural rubber content1 (HRC1). In the c112 mutant, the concentrations of NR precursors isopentenyl pyrophosphate and dimethylallyl diphosphate decreased, while geranylgeranyl diphosphate increased, suggesting that HRC1 regulates metabolic flux in NR biosynthesis. In summary, the developed TKS SARE mutant library provides valuable genetic resources for identifying key functional genes to accelerate the domestication of TKS from wild species to economic crops through molecular breeding.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".