Phytophthora infestans is the causal agent of late blight in potato. The occurrence of P. infestans with both A1 and A2 mating types in the field may result in sexual reproduction and the generation of recombinant strains. Such strains with new combinations of traits can be highly aggressive, resistant to fungicides, and can make the disease difficult to control in the field. Metalaxyl-resistant isolates are now more prevalent in potato fields. Understanding the genetic structure and rapid identification of mating types and metalaxyl response of P. infestans in the field is a prerequisite for effective late blight disease monitoring and management. Molecular and phenotypic assays involving molecular and phenotypic markers such as mating types and metalaxyl response are typically conducted separately in the studies of the genotypic and phenotypic diversity of P. infestans. As a result, there is a pressing need to reduce the experimental workload and more efficiently assess the aggressiveness of different strains. We think that employing genetic markers to not only estimate genotypic diversity but also to identify the mating type and fungicide response using machine learning techniques can guide and speed up the decision-making process in late blight disease management, especially when the mating type and metalaxyl resistance data are not available. This technique can also be applied to determine these phenotypic traits for dead isolates. In this study, over 600 P. infestans isolates from different populations—Estonia, Pskov region, and Poland—were classified for mating types and metalaxyl response using machine learning techniques based on simple sequence repeat (SSR) markers. For both traits, random forest and the support vector machine demonstrated good accuracy of over 70%, compared to the decision tree and artificial neural network models whose accuracy was lower. There were also associations (p < 0.05) between the traits and some of the alleles detected, but machine learning prediction techniques based on multilocus SSR genotypes offered better prediction accuracy.

Volatile organic compounds (VOCs) play key roles in plant abiotic and biotic stress resistance, but even for widespread crops, there is limited information on variations in the magnitude and composition of constitutive VOC emissions among cultivars with varying stress resistance. The foliage VOC emissions from nine local and commercial potato cultivars (Alouette, Sarme, Kuras, Ando, Anti, Jõgeva Kollane, Teele, 1681-11, and Reet) with medium to late maturities and varying Phytophthora infestans (the causative agent of late blight disease) resistance backgrounds were analyzed to gain an insight into the genetic diversity of constitutive VOC emissions and to test the hypothesis that cultivars more resistant to Phytophthora infestans have greater VOC emissions and different VOC fingerprints. Forty-six VOCs were identified in the emission blends of potato leaves. The majority of the VOCs were sesquiterpenes (50% of the total number of compounds and 0.5–36.9% of the total emissions) and monoterpenes (30.4% of the total number of compounds and 57.8–92.5% of the total VOC emissions). Qualitative differences in leaf volatiles, mainly in sesquiterpenes, were related to the potato genotype background. Among the volatile groups, the monoterpenes α-pinene, β-pinene, Δ³-carene, limonene, and p-cymene, the sesquiterpenes (E)-β-caryophyllene and α-copaene, and green leaf volatile hexanal were the major volatiles in all cultivars. A higher share of VOCs known to have antimicrobial activities was observed. Interestingly, the cultivars were grouped into high and low resistance categories based on the VOC profiles, and the total terpenoid and total constitutive VOC emission scale positively with resistance. To support and expedite advances in breeding for resistance to diseases such as late blight disease, the plant research community must develop a fast and precise approach to measure disease resistance. We conclude that the blend of emitted volatiles is a fast, non-invasive, and promising indicator to identify cultivars resistant to potato late blight disease.

The Estonia potato cultivar Ando has shown elevated field resistance to Phytophthora infestans, even after being widely grown for over 40 years. A comprehensive transcriptional analysis was performed using RNA-seq from plant leaf tissues to gain insight into the mechanisms activated for the defense after infection. Pathogen infection in Ando resulted in about 5927 differentially expressed genes (DEGs) compared to 1161 DEGs in the susceptible cultivar Arielle. The expression levels of genes related to plant disease resistance such as serine/threonine kinase activity, signal transduction, plant-pathogen interaction, endocytosis, autophagy, mitogen-activated protein kinase (MAPK), and others were significantly enriched in the upregulated DEGs in Ando, whereas in the susceptible cultivar, only the pathway related to phenylpropanoid biosynthesis was enriched in the upregulated DEGs. However, in response to infection, photosynthesis was deregulated in Ando. Multi-signaling pathways of the salicylic-jasmonic-ethylene biosynthesis pathway were also activated in response to Phytophthora infestans infection.

Knowledge of a pathogen’s genetic variability and population structure is of great importance to effective disease management. In this study, 193 isolates of Phytophthora infestans collected from three Estonian islands were characterized over 3 years using simple sequence repeat (SSR) marker data complemented by information on their mating type and resistance to metalaxyl. In combination with SSR marker data from samples in the neighboring Pskov region of Northwest Russia, the impact of regional and landscape structure on the level of genetic exchange was also examined. Among the 111 P. infestans isolates from Estonian islands, 49 alleles were detected among 12 SSR loci, and 59 SSR multilocus genotypes were found, of which 64% were unique. The genetic variation was higher among years than that among islands, as revealed by the analysis of molecular variance. The frequency of metalaxyl-resistant isolates increased from 9% in 2012 to 30% in 2014, and metalaxyl resistance was most frequent among A1 isolates. The test for isolation by distance among the studied regions was not significant, and coupled with the absence of genetic differentiation, the result revealed gene flow and the absence of local adaptation. The data are consistent with a sexual population in which diversity is driven by an annual germination of soilborne oospores. The absence of shared genotypes over the years has important implications when it comes to the management of diseases. Such population diversity can make it difficult to predict the nature of the outbreak in the coming year as the genetic makeup is different for each year.