Development of molecular genomic resources for Polymyxa betae

Authors: Martin, Frank; CAMELO GARCIA, VIVIANA - Forest Service (FS); Wintermantel, William - Bill

Submitted to: American Society of Sugar Beet Technologists
Publication Type: Other
Publication Acceptance Date: 10/16/2020
Publication Date: 3/2/2021
Citation: Martin, F.N., Camelo Garcia, V., Wintermantel, W.M. 2021. Development of molecular genomic resources for Polymyxa betae. American Society of Sugar Beet Technologists Annual Meeting, March 3, 2021 (virtual).

Interpretive Summary:

Technical Abstract: Polymyxa betae functions as a vector for several different soilborne viruses of sugar beet. Since it is an obligate pathogen, there are challenges for developing genomic resources to support further investigations with this fungus. The use of high throughput Illumina sequencing is one approach that can address these challenges. 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. Heavily infected roots were recovered from four geographically diverse isolates and the extracted DNA submitted for Illumina sequencing. The resulting reads were mapped against a reference library of the sugar beet genome to filter out host sequences and the remaining reads de novo assembled and mapped to P. betae reference sequence (isolate A26-41 from Belgium; GenBank RZBT01). Comparative genomics was used to identify polymorphic regions among the five genomes. Eighteen genotypic markers were tested on ten P. betae isolates; amplification reactions were performed using identical conditions and annealing temperature for all of them. 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 between the P. betae isolates. Currently, we are testing field samples from different sugar beet production areas to validate the marker set and subsequently use them for population studies in commercial production fields.