Development of quantitative detection method for Meloidogyne incognita by qPCR
DOI:
https://doi.org/10.14393/BJ-v36n1a2020-42265Keywords:
Diagnostics, Monitoring, Root-knot nematode, techniqueAbstract
The root-knot nematode (Meloidogyne spp.) is the most important plant-parasitic nematode genus, they are the most common and destructive pathogens in this group. They produce some of the most drastic symptoms in plants and can significantly reduce the yield of crops. In order to achieve deploy an efficient method of plant-parasitic nematode management, is necessary an identification and quantification accurate and reliable of plant-parasitic nematodes. The aim of this study was to analyze samples in qPCR to detect and quantify M. incognita, in the field samples, comparing different methods of extraction of DNA and its efficacy in establishing the number of individuals. For this purpose the effectiveness of different DNA methods of extraction was compared through the values of CT intervals. For standard curve and method comparisons, we used nematodes multiplied in a greenhouse and carefully separated in the specific quantities of the experiments. For the number of individuals experiment field samples previously counted under an optical microscope were used. The DNA extraction was made from 100 nematodes by the methods: CTAB, Phenol: Chloroform and commercial kit (PureLink® Genomic DNA Kit, Invitrogen). In the comparative analysis using the three methods of DNA extracting from 100 nematodes, it was observed that commercial kit and CTAB methods obtained CT values similar. The CTAB method of extraction, showed less variation in the repeats and greater linearity of standard curve in comparison with other methods tested. So, it was possible to quantify the samples through the CT value intervals, established from different numbers of individuals (1, 10, 25, 100, 250, 500 and 750), in field samples. This study demonstrated that qPCR technique is an alternative sensitive and reliable for the quantification of M. incognita to support laboratories of diagnose and field survey.
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Copyright (c) 2020 Camilla Martins de Oliveira, Ismail Teodoro de Souza Júnior, Nayane Oliveira Almeida, Marcos Augusto de Freitas, Mara Rúbia da Rocha, Silvana Petrofeza
This work is licensed under a Creative Commons Attribution 4.0 International License.