Genome-Wide Genetic Architecture for Common Scab (Streptomyces scabei L.) Resistance in Diploid Potatoes
Bibliographic record
Abstract
Most cultivated potato (Solanum tuberosum) varieties are highly susceptible to common scab (Streptomyces scabei). The disease is widespread in all major potato production areas and leads to high economic losses and food waste. Varietal resistance is seen as the most viable and sustainable long-term management strategy. However, resistant potato varieties are scarce, and their genetic architecture and resistance mechanisms are poorly understood. Moreover, diploid potato relatives to commercial potatoes remain to be fully explored. In the current study, a panel of 384 ethyl methane sulfonate (EMS)-mutagenized diploid potato clones were evaluated for common scab coverage, severity, and incidence traits under field conditions, and genome-wide association studies (GWASs) were conducted to dissect the genetic architecture of their traits. Using the GAPIT-MLM and RTM-GWAS statistical models, and Mann–Whitney non-parametric U-tests, we show that 58 QTNs/QTLs distributed on all 12 potato chromosomes were associated with common scab resistance, 52 of which had significant allelic effects on the three traits. In total, 38 of the 52 favorable QTNs/QTLs were found to be pleiotropic on at least two of the traits, while 14 were unique to a single trait and were found distributed over 3 chromosomes. The identified QTNs/QTLs showed low to high effects, highlighting the quantitative and multigenic inheritance of common scab resistance. The QTLs/QTNs associated with the three common scab traits were found to be co-located in genomic regions carrying 79 candidate genes playing roles in plant defense, cell wall component biosynthesis and modification, plant–pathogen interactions, and hormone signaling. A total of 61 potato clones were found to be tolerant or resistant to common scab. Taken together, the data show that the studied germplasm panel, the identified QTNs/QTLs, and the candidate genes are prime genetic resources for breeders and biologists in breeding and targeted gene editing.
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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 | 0.000 | 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) | 0.002 | 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".