<scp>PRpnp</scp>, a novel dual activity <scp>PNP</scp> family protein improves plant vigour and confers multiple stress tolerance in <i>Citrus aurantifolia</i>
Bibliographic record
Abstract
Under field conditions, plants are often simultaneously exposed to several abiotic and biotic stresses resulting in significant reductions in growth and yield; thus, developing a multi-stress tolerant variety is imperative. Previously, we reported the neofunctionalization of a novel PNP family protein, Putranjiva roxburghii purine nucleoside phosphorylase (PRpnp) to trypsin inhibitor to cater to the needs of plant defence. However, to date, no study has revealed the potential role and mechanism of either member of this protein group in plant defence. Here, we overexpressed PRpnp in Citrus aurantifolia which showed nuclear-cytoplasmic localization, where it functions in maintaining the intracellular purine reservoir. Overexpression of PRpnp significantly enhanced tolerance to salt, oxidative stress, alkaline pH, drought and two pests, Papilio demoleus and Scirtothrips citri in transgenic plants. Global gene expression studies revealed that PRpnp overexpression up-regulated differentially expressed genes (DEGs) related to ABA- and JA-biosynthesis and signalling, plant defence, growth and development. LC-MS/MS analysis validated higher endogenous ABA and JA accumulation in transgenic plants. Taken together, our results suggest that PRpnp functions by enhancing the endogenous ABA and JA, which interact synergistically and it also inhibits trypsin proteases in the insect gut. Also, like other purine salvage genes, PRpnp also regulates CK metabolism and increases the levels of CK-free bases in transgenic Mexican lime. We also suggest that PRpnp can be used as a potential candidate to develop new varieties with improved plant vigour and enhanced multiple stress resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".