105(3)_str34

 

ISSN 1392-3196 / e-ISSN 2335-8947
Zemdirbyste-Agriculture, vol. 105, No. 3 (2018), p. 265–270
DOI  10.13080/z-a.2018.105.034

Genetic diversity of Botrytis cinerea from strawberry in Lithuania

Neringa RASIUKEVIČIŪTĖ, Rytis RUGIENIUS, Jūratė Bronė ŠIKŠNIANIENĖ

Abstract

Botrytis cinerea Pers.: Fr is an important strawberry disease-causing pathogen with a broad host range. Classical B. cinerea identification is complicated due to the lack of morphological polymorphism between species. The use of molecular tools helps to identify pathogens fast and accurately. This study aimed to determine Botrytis spp. isolates and evaluate the genetic diversity of grey mould population in Lithuania. During June–August of 2012–2014, 273 isolates were sampled from 12 different areas of Lithuania. All samples were isolated from infected fruits, and single-spore isolates were extracted. B. cinerea isolates were identified using B. cinerea species-specific primers Bc108+ / Bc563. The polymerase chain reaction (PCR) showed two bands characteristic of two specific DNA fragments of B. cinerea – upper and lower band of 360 and 480 bp, respectively. These two bands reflect pathogen genotype differentiation and could be used for cryptic species detection. The cryptic species analysis revealed that resistant group I accounted for 16.95% and sensitive group II for 83.05% of the Lithuanian collection of B. cinerea isolates. The precise identification of the B. cinerea cryptic species is important for the species-specific fungicide resistance and aggressiveness. Four microsatellite markers used in this study revealed genetic diversity of B. cinerea. The 158 isolates were identified as B. cinerea. The most polymorphic microsatellite marker was BC6 (0.88) and the least polymorphic – BC7 (0.79). The isolates clustered into three genetic groups. The first group consisted of 45 strains, the second group of 15 and the third group of 4 isolates. Our data show genetic diversity within the Lithuanian population of B. cinerea. One of the management tools is recognition and identification of the pathogen which leads to optimal and efficient disease management.

Key words: grey mould, identification, pathogen, polymorphism.

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