Pathogen genetics identifies avirulence/virulence loci associated with barley chromosome 6H resistance in the <i>Pyrenophora teres</i> f. <i>teres</i> – barley interaction
Bibliographic record
Abstract
Abstract Barley net form net blotch (NFNB) is a foliar disease caused by Pyrenophora teres f. teres . Barley line CIho5791, which harbors the chromosome 6H broad spectrum resistance gene Rpt5 , displays dominant resistance to P. teres f. teres . To genetically characterize P. teres f. teres avirulence/virulence on the barley line CIho5791, we generated a P. teres f. teres mapping population using a cross between the Moroccan CIho5791-virulent isolate MorSM40-3, and the avirulent reference isolate 0-1. Genetic maps were generated for all 12 chromosomes (Ch) and quantitative trait locus (QTL) mapping identified two significant QTL associated with P. teres f. teres avirulence/virulence on CIho5791. The most significant QTL mapped to P. teres f. teres Ch1 where the virulent allele was contributed by MorSM40-3. A second QTL mapped to Ch8, however, this virulent allele was contributed by 0-1. The Ch1 and Ch8 loci accounted for 27 and 15% of the disease variation, respectively and the avirulent allele at the Ch1 locus was shown to be epistatic over the virulent allele at the Ch8 locus. Additionally, we used 177 sequenced P. teres f. teres isolates in a genome wide association study that identified the same Ch1 and Ch8 loci as the two most significant associations. Within the identified genomic regions, we identified several genes that encoded small secreted proteins, one or more of which may be responsible for overcoming the CIho5791 resistance. Results presented here demonstrate the complexity of avirulence/virulence in the P. teres f. teres - barley interaction.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".