Hairpin RNA derived from viral NIa gene confers immunity to wheat streak mosaic virus infection in transgenic wheat plants
Bibliographic record
Abstract
Wheat streak mosaic virus (WSMV), vectored by Wheat curl mite, has been of great economic importance in the Great Plains of the United States and Canada. Recently, the virus has been identified in Australia, where it has spread quickly to all major wheat growing areas. The difficulties in finding adequate natural resistance in wheat prompted us to develop transgenic resistance based on RNA interference (RNAi). An RNAi construct was designed to target the nuclear inclusion protein 'a' (NIa) gene of WSMV. Wheat was stably cotransformed with two plasmids: pStargate-NIa expressing hairpin RNA (hpRNA) including WSMV sequence and pCMneoSTLS2 with the nptII selectable marker. When T(1) progeny were assayed against WSMV, ten of sixteen families showed complete resistance in transgenic segregants. The resistance was classified as immunity by four criteria: no disease symptoms were produced; ELISA readings were as in uninoculated plants; viral sequences could not be detected by RT-PCR from leaf extracts; and leaf extracts failed to give infections in susceptible plants when used in test-inoculation experiments. Southern blot hybridization analysis indicated hpRNA transgene integrated into the wheat genome. Moreover, accumulation of small RNAs derived from the hpRNA transgene sequence positively correlated with immunity. We also showed that the selectable marker gene nptII segregated independently of the hpRNA transgene in some transgenics, and therefore demonstrated that it is possible using these techniques, to produce marker-free WSMV immune transgenic plants. This is the first report of immunity in wheat to WSMV using a spliceable intron hpRNA strategy.
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 | 0.001 |
| 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".