Genetic Characterization of Resistance to Pyrenophora teres f. teres in the International Barley Differential Canadian Lake Shore
Bibliographic record
Abstract
Genetic resistance to net form of net blotch (NFNB) in the international barley differential Canadian Lake Shore (CLS) was characterized and mapped. A doubled haploid (DH) population generated from a cross between CLS and susceptible cultivar Harrington was evaluated at the seedling stage using eight diverse Pyrenophora teres f. teres (Ptt) isolates and at the adult stage in the field using natural inoculum. To effectively map the CLS resistance, comparative marker frequency analysis (MFA) was performed using 8,762 polymorphic DArT-seq markers, where ‘resistant’ and ‘susceptible’ groups each comprised 40 DH lines displaying the most extreme phenotypes. Five DArTseq markers were consistently detected in eight disease assays, which was designated qPttCLS and deemed to harbor the locus underpinning CLS resistance. Four of these markers were present onto the barley DArTseq physical map and spans a region between 398203862 – 435526243 bp which were found to consist several genes involved in important plant functions such as disease response and signaling pathways. While MFA only detected the 3H region, genetic analyses based on segregation patterns were inconsistent, suggesting complex inheritance or variation in phenotypic expression of qPttCLS, particularly in the field. This study represents progress towards connecting Ptt pathotype surveys with the corresponding resistance genes in barley differentials. The markers associated with qPttCLS are useful for marker-assisted selection in breeding programs.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".