Untying the knot: Unraveling genetic mechanisms behind black knot disease resistance in <i>Prunus salicina</i> (Japanese plum)
Bibliographic record
Abstract
Abstract Little is known regarding the genes, compounds and physiological alternations that take place upon infection of black knot disease. This research aimed to unravel the genetic mechanism responsible for the resistance of Japanese plum ( Prunus salicina L.) trees against black knot ( Apiosporina morbosa Schwein.) using a Genome‐Wide Association Study. Genotyping by Sequencing (GBS) was combined with a phenotyping system to analyze 200 genotypes of mixed origin. Population stratification identified four subpopulations, and the Fixed and Random Model Circulating Probability Unification (FarmCPU) algorithm was used for this analysis. Nineteen single nucleotide polymorphisms (SNPs) significantly associated with black knot disease resistance were discovered across five chromosomes. Linkage disequilibrium analysis identified 55 genes near these SNPs, with eight genes related to plant defense, immunity, and biotic stress response. One SNP mutation was found in the 5′ untranslated region of a gene regulating the first enzyme in phenylpropanoid biosynthesis. The results provide valuable insights into the genetic mechanisms behind BLACK KNOT disease resistance in Japanese plum and identifies potential markers for use in molecular breeding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".