1Central Laboratory, Gorgan University of Agricultural Sciences and Natural Resourses, Gorgan, Iran.
2College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
Pear decline is a very important phytoplasma disease that causes considerable quantitative and qualitative losses to this fruit crop. Due to economical importance of pear in Isfahan province, Iran, and the difficulty to determine the occurrence of the disease simply based on symptoms in orchards, a detection method for the phytoplasma causing disease in pears in the region was developed. Since the polymerase chain reaction (PCR) assay is a reliable and sensitive technique for identification of phytoplasma, nested-PCR method were employed which is included different sets of universal and specific primer pairs. Using P1/P7 together with fU5/rU3, or NPA2F/R in nested-PCR, products of the expected sizes were obtained from only 25% of the symptomatic samples. To examine the variation between phytoplasmal isolates from Isfahan and other countries, and to design a specific primer pair for the Iranian isolates, the PCR product from one of the samples, was sequenced. The BLASTN results showed high similarity to Knautia arvensis associated phytoplasma (99%). Significant homology also was found with phytoplasmas of almond witches' broom (96%), peach X disease (93%), pear decline (94%) and apple proliferation (92%). Having confirmed that there is a variation between the sequence of local phytoplasmas and similar pathogens deposited in the database, a pair of primers (fPD/rPD) were designed from the sequence using OLIGO software to increase the sensitivity of nested-PCR for detection of pear associated phytoplasma in Isfahan. In further experiments, using specific designed primers, the pathogen was detected in 72% of the samples. These primers are vastly introduced to improve the limit of detection and the specificity of the tests for the detection of pear phytoplasmas in the region.