Genome-Wide Genetic Architecture for Common Scab (Streptomyces scabei L.) Resistance in Diploid Potatoes

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.

Keywords: GWAS; Streptomyces scabei; candidate genes; common scab; diploid potato; disease resistance.

Figure 1

(A–E) Common scab severity distribution among the 384 germplasm panel; (A) spatial visual distribution of individuals for scab disease severity rating classes; (B) scatter box plot of average distribution; (C) frequency distribution of individuals for scab severity ratings; (D) density plot of individuals for scab severity ratings; and (E) cummulative density distribution for scab severity ratings.

Figure 2

(A–E) Common scab coverage phenotype distribution among the 384 germplasm panel; (A) spatial visual distribution of individuals for scab disease coverage rating classes; (B) scatter box plot of average distribution; (C) frequency distribution of individuals for scab coverage ratings; (D) density plot of individuals for scab coverage ratings; and (E) cummulative density dstribution for scab coverage ratings.

Figure 3

(A–E) Common scab incidence distribution among the 384 germplasm panel; (A) spatial visual distribution of individuals for scab disease incidence rating classes; (B) scatter box plot of average distribution; (C) frequency distribution of individuals for scab incidence ratings; (D) density plot of individuals for scab incidence ratings; and (E) cummulative density disstribution for scab incidence ratings.

Figure 4

Principal component analysis of the 2021–2023 dataset depicting the differentiation among the 68 clones most contrasting for common scab reaction. Three groups can be observed. Green: low rating for incidence, severity, and surface coverage. Red: high rating for incidence, severity, and surface coverage. Orange: low to medium rating. The red grouping is closely associated with high incidence, severity, and coverage. Note that the sample IDs may be found overlaped and are not intended to be readable in each group.

Figure 5

(A–C) Manhattan and Q-Q plots showing QTNs/QTLs and chromosomal regions associated with common scab traits using the GAPIT-MLM. Each panel corresponds two datasets (mean and BLUP). (A) Coverage mean and BLUP; (B) severity mean and BLUP; and (C) incidence mean and BLUP. The dotted line indicates the cut off −log₁₀(p) < 2.5. The six boxed inserts on the right present the quantile–quantile (Q-Q) plot for each Manhattan plot, showing a well-fitted GWAS model, with minimal artifact bias from −log₁₀(p) values > 2.5. The blue dots represent the p-values observed from the genomic association study. The red line is the expected distribution of p-values when there is no association under the null hypothesis. It acts as a reference line to assess if the data deviate significantly from the expected distribution. Since most tested SNPs may not be associated with the trait, the majority of blue dots in the Q-Q plot should fall on the red line, indicative of a good fit to the null hypothesis, as shown. The deviations from the red line suggest potential significant associations. The gray area indicates the 95% confidence interval under the null.

Figure 6

(A–C) Violin plots illustrating the phenotypic differences between potato genotypes carrying different alleles of the significant SNPs. (A) Scab incidence, (B) scab severity, and (C) scab coverage. Means and standard variations for each SNP allele are shown. Statistical differences between alleles were tested using the Mann–Whitney non-parametric U test (p < 0.05).

Figure 7

(A,B) Heatmap and violin plots displaying positive and negative allelic effects among 40 potato clones with differential common scab reactions. (A) Heatmap displaying the distribution of 32 unique positive QTL (PQTL) alleles among 20 high and 20 low potato clones carrying more or fewer PQTLs; (B) violin plots illustrating the mean of favorable PQTL for the best potato genotypes carrying 18 PQTLs and the worst genotypes carrying 5.6 PQTLs for each common scab trait.