Virus-Induced LeSPL-CNR Silencing Inhibits Fruit Ripening in Tomato
Bibliographic record
Abstract
Fruit ripening is a developmentally and genetically programmed process. In tomato (Solanum lycopersicum), ripening determines fruit quality, commodity value, shelf life and many important attributes. To understand this intricate process and its underpinning mechanism, an efficient and effective approach for screening and functional analysis of ripening-associated genes (RAGs) is required. Virus-induced gene silencing (VIGS) is a powerful reverse genetics tool for uncovering gene functions in plants. VIGS has been exploited to investigate roles of RAGs in tomato ripening. However in most cases, virus-induced RAG silencing is only assessed and correlated with the chromatic change of fruits. Here we report that silencing of LeSPL-CNR through a Potato virus X-based VIGS inhibited fruit ripening and led to development of non-ripening sectors in Ailsa Craig (AC) tomatoes. Non-ripening sectors remained firmer and possessed greater relative electric conductivity and acidity as well as a higher amount of chlorophyll, but a lower quantity of anthocyanin. VIGS of LeSPL-CNR also affects expression of other key RAGs and genes associated with biogenesis of ripening hormone ethylene. These findings indicate that AC fruits undergoing VIGS of LeSPL-CNR phenocopied physical, physiological, agrochemical, biochemical and molecular characteristics of the Colourless non-ripening epimutant. Thus, the overall phenotypical changes from visual appearance to RAG expression caused by LeSPL-CNR silencing reaffirm the great usefulness of VIGS to reveal biological functions of genes crucial in tomato ripening and fruit quality.
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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 | 0.001 |
| 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".