Determining Whether Geographic Origin and Potato Genotypes Shape the Population Structure of <i>Phytophthora infestans</i> in the Central Region of Colombia

Chaves, Sandra Catalina; Rodríguez, María Camila; Mideros, María Fernanda; Lucca, Florencia; Ñústez, Carlos Eduardo; Restrepo, Silvia

doi:10.1094/phyto-05-18-0157-r

Cited by 5 publications

(1 citation statement)

References 63 publications

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“…Yield loss and protection against late blight on average cost approximately six billion USD worldwide [1,2]. Despite intense efforts to control the disease, P. infestans remains a major threat to potato and tomato production [3].…”

Section: Introductionmentioning

confidence: 99%

Population Structure of Phytophthora infestans from a Single Location in Poland Over a Long Period of Time in Context of Weather Conditions

et al. 2020

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Phytophthora infestans (Mont.) de Bary is a destructive potato pathogen. Changing weather conditions are among the factors that influence the pathogen population structure. In this study, 237 P. infestans isolates were collected from a single unprotected experimental field in an area with high late-blight pressure located in Boguchwała in the southeastern part of Poland during 15 growing seasons (2000–2014). The isolates were assessed for mating type, mitochondrial haplotype, resistance to metalaxyl, virulence, and polymorphism of 14 single-sequence repeat markers (SSRs). The results revealed 89 unique genotypes among the 237 P. infestans isolates. Eighty-seven isolates belonged to genotype 34_A1, which was detected in all the years of research except 2012. Isolates of P. infestans from individual years were very similar to each other, as shown by Nei’s genetic identity based on 14 SSR markers. The obtained results on isolate characteristics were analyzed in terms of meteorological data (air temperature and precipitation) and indicated that frost, long winters, and hot, dry summers did not directly affect the P. infestans population structure. We described the variability in metalaxyl resistance and virulence among isolates of the P. infestans genotype 34_A1.

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Section: Introductionmentioning

confidence: 99%

Population Structure of Phytophthora infestans from a Single Location in Poland Over a Long Period of Time in Context of Weather Conditions

et al. 2020

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A machine learning algorithm for the automatic classification of Phytophthora infestans genotypes into clonal lineages

Patarroyo,

Dupas,

Restrepo

2024

Appl Plant Sci

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PremiseThe prompt categorization of Phytophthora infestans isolates into described clonal lineages is a key tool for the management of its associated disease, potato late blight. New isolates of this pathogen are currently classified by comparing their microsatellite genotypes with characterized clonal lineages, but an automated classification tool would greatly improve this process. Here, we developed a flexible machine learning–based classifier for P. infestans genotypes.MethodsThe performance of different machine learning algorithms in classifying P. infestans genotypes into its clonal lineages was preliminarily evaluated with decreasing amounts of training data. The four best algorithms were then evaluated using all collected genotypes.ResultsmlpML, cforest, nnet, and AdaBag performed best in the preliminary test, correctly classifying almost 100% of the genotypes. AdaBag performed significantly better than the others when tested using the complete data set (Tukey HSD P < 0.001). This algorithm was then implemented in a web application for the automated classification of P. infestans genotypes, which is freely available at https://github.com/cpatarroyo/genotypeclas.DiscussionWe developed a gradient boosting–based tool to automatically classify P. infestans genotypes into its clonal lineages. This could become a valuable resource for the prompt identification of clonal lineages spreading into new regions.

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Screening South American Potato Landraces and Potato Wild Relatives for Novel Sources of Late Blight Resistance

et al. 2022

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Late blight (LB) caused by the oomycete Phytophthora infestans is one of the most important biotic constraints for potato production worldwide. This study assessed 508 accessions (79 wild potato species and 429 landraces from a cultivated core collection) held at the International Potato Center (CIP) genebank for resistance to LB. One P. infestans isolate belonging to the EC-1 lineage, which is currently the predominant type of P. infestans in Peru, Ecuador, and Colombia, was used in whole plant assays under greenhouse conditions. Novel sources of resistance to LB were found in accessions of Solanum albornozii, S. andreanum, S. lesteri, S. longiconicum, S. morelliforme, S. stenophyllidium, S. mochiquense, S. cajamarquense, and S. huancabambense. All of these species are endemic to South America, and thus, could provide novel sources of resistance to potato breeding programs. We found that the level of resistance to LB in wild species and potato landraces cannot be predicted using altitude and bioclimatic variables of the locations where the accessions were collected. The high percentage (73%) of susceptible potato landraces to LB in our study suggests the importance of implementing disease control measurements, including planting susceptible genotypes in less-humid areas/seasons, or switching to genotypes identified as resistant. In addition, this study points out a high risk of genetic erosion in potato biodiversity in high altitudes of the Andes due to susceptibility to LB in the native landraces, which has been exacerbated by climatic change that favors the development of LB in those regions.

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Determining Whether Geographic Origin and Potato Genotypes Shape the Population Structure of Phytophthora infestans in the Central Region of Colombia

Cited by 5 publications

References 63 publications

Population Structure of Phytophthora infestans from a Single Location in Poland Over a Long Period of Time in Context of Weather Conditions

Population Structure of Phytophthora infestans from a Single Location in Poland Over a Long Period of Time in Context of Weather Conditions

A machine learning algorithm for the automatic classification of Phytophthora infestans genotypes into clonal lineages

Screening South American Potato Landraces and Potato Wild Relatives for Novel Sources of Late Blight Resistance

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