Heritable, De Novo Resistance to Leaf Rust and Other Novel Traits in Selfed Descendants of Wheat Responding to Inoculation with Wheat Streak Mosaic Virus
Bibliographic record
Abstract
Stable resistance to infection with Wheat streak mosaic virus (WSMV) can be evolved de novo in selfing bread wheat lines subjected to cycles of WSMV inoculation and selection of best-performing plants or tillers. To learn whether this phenomenon might be applied to evolve resistance de novo to pathogens unrelated to WSMV, we examined the responses to leaf rust of succeeding generations of the rust- and WSMV-susceptible cultivar 'Lakin' following WSMV inoculation and derived rust-resistant sublines. After three cycles of the iterative protocol five plants, in contrast to all others, expressed resistance to leaf and stripe rust. A subset of descendant sublines of one of these, 'R1', heritably and uniformly expressed the new trait of resistance to leaf rust. Such sublines, into which no genes from a known source of resistance had been introgressed, conferred resistance to progeny of crosses with susceptible parents. The F1 populations produced from crosses between, respectively, susceptible and resistant 'Lakin' sublines 4-3-3 and 4-12-3 were not all uniform in their response to seedling inoculation with race TDBG. In seedling tests against TDBG and MKPS races the F2s from F1 populations that were uniformly resistant had 3∶1 ratios of resistant to susceptible individuals but the F2s from susceptible F1 progenitors were uniformly susceptible. True-breeding lines derived from resistant individuals in F2 populations were resistant to natural stripe and leaf rust inoculum in the field, while the 'Lakin' progenitor was susceptible. The next generation of six of the 'Lakin'-derived lines exhibited moderate to strong de novo resistance to stem rust races TPMK, QFCS and RKQQ in seedling tests while the 'Lakin' progenitor was susceptible. These apparently epigenetic effects in response to virus infection may help researchers fashion a new tool that expands the range of genetic resources already available in adapted germplasm.
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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".