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ARS Home » Pacific West Area » Salinas, California » Crop Improvement and Protection Research » Research » Publications at this Location » Publication #384141
Research Project: Management of Pathogens for Strawberry and Vegetable Production Systems

Location: Crop Improvement and Protection Research

Title: Development of molecular methods for genotyping isolates of Polymyxa betae

Author
item CAMELO-GARCIA, VIVIANA - Us Forest Service (FS)
item Martin, Frank
item Wintermantel, William - Bill

Submitted to: American Phytopathological Society Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 4/15/2021
Publication Date: 8/2/2021
Citation: Camelo-Garcia, V., Martin, F.N., Wintermantel, W.M. 2021. Development of molecular methods for genotyping isolates of Polymyxa betae. American Phytopathological Society Annual Meeting, August 2-6, 2021 (virtual).

Interpretive Summary:

Technical Abstract: Despite the fact that Polymyxa betae is a vector of different soil-borne viruses that cause important diseases in sugar beet, it is still poorly studied. High throughput Illumina sequencing and comparative genomics were used to develop molecular methods for genotyping isolates of P. betae. A single cystosorus culture collection was established for a range of isolates recovered from soil samples collected from sugar beet growing areas across the U.S.A. DNA from heavily infected roots from seven geographically diverse isolates were submitted for Illumina sequencing. Comparative genomics, using a Belgium isolate as reference sequence, was used to identify polymorphic regions among the eight genomes. Eighteen genotyping markers were tested on ten P. betae isolates, most of the primers tested performed well and the amplicons obtained were sequenced. Multiple sequence alignments identified polymorphisms in the sequences obtained with a set of twelve primer pairs. A total of 132 DNA sequences were concatenated, including the reference sequence, for each locus. The Neighbor-Joining method was used for phylogenetic reconstruction as implemented in Geneious 2020.2.3 and network analysis was performed using the neighborNet method from the SplitsTree5 software. Both analyzes showed different clades independent of the geographic origin, revealing genetic variability among the P. betae isolates. Currently, we are testing field samples from sugar beet production areas to validate the marker set for population studies in commercial production fields.