High-Resolution Melting (HRM) Analysis Reveals Genotypic Differentiation of Venturia inaequalis Populations in Greece

Frontiers in Ecology and Evolution

Panagiota Panagiotaki¹  Olga Ntantali¹  Ioannis Ganopoulos²  Evangelos K. Vellios³  Michael Chatzidimopoulos³  Fenia Lioliopoulou³  Eleni Moraitou-Daponta³ 

[1] Department of Ichthyology and Aquatic Environment, University of Thessaly, Volos, Greece;Hellenic Agricultural Organization ‘Demeter’, Institute of Plant Breeding and Genetic Resources, Thessaloniki, Greece;Laboratory of Plant Pathology, Department of Agriculture, Crop Production and Rural Environment, University of Thessaly, Volos, Greece;

关键词: HRM;    SSR;    Venturia inaequalis;    apple scab;    population genetics;   

DOI  :  10.3389/fevo.2019.00489

来源: DOAJ

【 摘 要 】

During the recent years, High Resolution Melting (HRM) analysis has been developed as a rapid and accurate tool in plant disease diagnostics, species identification and SNP genotyping. This approach has been applied to analyze the genetic diversity in several plant species with molecular markers, including single sequence repeats (SSR). However, no studies have been carried out to investigate the variation of SSR in plant pathogenic fungi by using the HRM technology. In this report, the genetic structure of Venturia inaequalis populations in Greece was investigated for the first time by using six microsatellite markers. The developed HRM protocol was able to generate genotype-specific melting curves, consistent with the haploid nature of the fungus. Unknown samples were genotyped using standard samples as reference controls among multiple runs. Compared to the more complex genome of diploid plants, several limitations were avoided. The shape of the melting curves revealed differences between the genotypes in each SSR marker and showed that all the genotypes could be easily distinguished. The genetic analysis of apple scab populations revealed high genetic variation within the populations (96%), while only 4% of the total gene diversity was attributed to among-population variation. The isolates were grouped into three higher-level populations according to the principal coordinate analysis (PCoA).

【 授权许可】

Unknown