Genetic dissection and identification of stripe rust resistance genes in the wheat cultivar Lanhangxuan 121, a cultivar selected from a space mutation population
Bibliographic record
Abstract
Abstract Stripe rust is a devastating disease of wheat worldwide. Chinese wheat cultivar Lanhangxuan 121 (LHX121), selected from an advanced line L92-47 population that had been subjected to space mutation breeding displayed a consistently higher level of resistance to stipe rust than its parent in multiple field environments. The aim of this research was to establish the number and types of resistance genes L92-47 and LHX121 using separate segregating populations. The first population developed from a cross between LHX121 and susceptible cultivar Xinong 822 comprised 278 F2:3 lines. The second validation population comprised 301 F2:3 lines from a cross between L92-47 and susceptible cultivar Xinong 979. These lines were evaluated for stripe rust response at three sites during the 2018-2020 cropping season. Affymetrix 660K SNP arrays were used to genotype the lines and parents. Inclusive composite interval mapping detected QTL QYrLHX.nwafu-2BS, QYrLHX.nwafu-3BS, and QYrLHX.nwafu-5BS for resistance in all three environments. Based on previous studies and pedigree information, QYrLHX.nwafu-2BS and QYrLHX.nwafu-3BS were likely to be Yr27 and Yr30 that are present in the L92-47 parent. QYrLHX.nwafu-5BS (YrL121) detected only in LHX121 was mapped to a 7.60 cM interval and explained 10.67-22.57% of the phenotypic variation. Compared to stripe rust resistance genes previously mapped to chromosome 5B, YrL121 might be a new adult plant resistance QTL. Further, there were a number of variations signals using 35K SNP array and differentially expressed genes using RNA-seq between L92-47 and LHX121 in the YrL121 region, indicating that they probably impair the presence and/or function of YrL121.
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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 | 0.001 | 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 | 0.000 |
| 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".