Determination of differences of DNA sequencing between avirulent and Mi-1 virulent populations of Meloidogyne incognita (Kofoid & White, 1919) chitwood, 1949 by next generation sequencing methods

Tomato is one of the most important vegetables cultivated. Root-knot nematodes (RKNs) attack tomato plants and cause yield losses. The tomato plants which are resistant to Meloidogyne spp. are commonly used for controlling root-knot nematodes in the tomato growing areas. The Mi-1 gene in tomato controls resistance to Meloidogyne incognita, M. arenaria, M. javanica and M. luci. However, virulent root-knot nematode populations can overcome the Mi-1 gene. Mi-1 virulent RKNs are a major problem in tomato growing areas and are becoming increasingly common. Therefore, rapid and accurate identification of virulent RKN populations is needed in fields infested with RKNs. Traditional tests to identify virulent nematode populations in laboratory take up to 3-6 months. Therefore, it takes time and requires much labor. Whereas molecular markers linked virulence, it will be able to shorten the analysis time. For this reason, the development of molecular markers linked virulence is necessary for management of RKNs. In this study, the whole genome analyses of three avirulent M. incognita and three Mi-1 virulent M. incognita populations from Turkey were sequenced using Illumina HiSeq X10 150 bp paired-end sequencing techniques. The adapter sequences and the short and low quality readings were removed from raw data for bioinformatical analysis. Five approaches were then used in bioinformatics analysis. First, the sequences were mapped to M. incognita reference genome (GCA_900182535.1) and SNPs or INDELs were identified. A total of 17512 polimorphisms were detected only in Mi-1 virulent isolates. Second, common 229696 variants identified in all isolates were removed from data. Third, the remaining differences were then filtered according to the reading depths (DP≥20). As a result, 12122 variants that could be related to Mi-1 virulence were identified in the virulent populations. Results also showed that these differences obtained from isolates can correlate with 207 genes. Fourth, "de novo" analyse was performed on N1 isolate. This isolate was chosen as the reference genome and variants were investigated. Results showed that this last approach did not provide additional information according to data obtained using M. incognita reference genome. The fifth approach, DNA sequencings from avirulent and virulent isolates were analysed using different bioinformatic tools and 161 SNP that will be associated with virulence were identified. This is the first study to identify virulent and avirulent RKNs using next generation sequencing in Turkey. The identified SNPs and INDELs can be used for development of molecular markers linked virulence in the future studies.