Genetic variability and population structure of Pseudocercospora griseola isolates in the Black Sea region of Türkiye

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发表日期：

2024年9月18日

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Sirel Canpolat,
Duygu Mermer Doğu,
Gülsüm Palacıoğlu

摘要

Angular leaf spot caused by Pseudocercospora griseola is one of the most common diseases of bean-grown areas in the world. Knowing the genetic structure of the pathogens enables the development of disease control strategies. The purpose of this study was to analyze genetic variability and population structure of 63 Pseudocercospora griseola isolates collected from greenhouses in Black Sea region of Türkiye. Twenty-seven iPBS and thirty-six SCoT primers were assessed to visualize genetic variation among isolates, and four primers from each marker were used for the entire study. The mean percentage of resolving power per primer was 1.10 and 0.73 for iPBS and SCoT markers, respectively. The dendrogram obtained from the combined dataset of both marker systems divided the isolates into two main groups with a genetic similarity of 92%, which is partially associated with the geographical origin of the isolates. The dendrogram of Nei's genetic distances separated the Zonguldak population from all other populations. Karabük and Bartın were grouped, while Ordu and Giresun departed from these populations. STRUCTURE analysis supported with the highest mean value of Ln likelihood (ΔK = 4; LnP(K) = -432.0) the distribution of P. griseola populations based on the Nei’s dendrogram. The mean genetic differentiation (G_ST) among all populations was a high level at 0.429, but there was a low level of gene flow (N_M) at 0.665. AMOVA analysis showed that 58% of genetic variation was between the isolates within populations, and 42% was among populations. iPBS and SCoT markers were tested for the first time to assess intraspecific variation among the isolates of P. griseola. Both methods were easy to use and gave us detailed and consistent information about the genetic diversity of P. griseola. The results from the study proved that these markers are useful and effective tools in analyzing the genetic structure of P. griseola.