Prevalence and Distribution of Beet Necrotic Yellow Vein Virus Strains in North Dakota and Minnesota.
John J WeilandKathrin BornemannJonathan D NeubauerMohamed F R KhanMelvin D BoltonPublished in: Plant disease (2019)
Beet necrotic yellow vein virus (BNYVV) is the causal agent of rhizomania, a disease of global importance to the sugar beet industry. The most widely implemented resistance gene to rhizomania to date is Rz1, but resistance has been circumvented by resistance-breaking (RB) isolates worldwide. In an effort to gain greater understanding of the distribution of BNYVV and the nature of RB isolates in Minnesota and eastern North Dakota, sugar beet plants were grown in 594 soil samples obtained from production fields and subsequently were analyzed for the presence of BNYVV as well as coding variability in the viral P25 gene, the gene previously implicated in the RB pathotype. Baiting of virus from the soil with sugar beet varieties possessing no known resistance to rhizomania resulted in a disease incidence level of 10.6% in the region examined. Parallel baiting analysis of sugar beet genotypes possessing Rz1, the more recently introgressed Rz2, and with the combination of Rz1 + Rz2 resulted in a disease incidence level of 4.2, 1.0, and 0.8%, respectively. Virus sequences recovered from sugar beet bait plants possessing resistance genes Rz1 and/or Rz2 exhibited reduced genetic diversity in the P25 gene relative to those recovered from the susceptible genotype while confirming the hypervariable nature of the coding for amino acids (AAs) at position 67 and 68 in the P25 protein. In contrast to previous reports, we did not find an association between any one specific AA signature at these positions and the ability to circumvent Rz1-mediated resistance. The data document ongoing virulence development in BNYVV populations to previously resistant varieties and provide a baseline for the analysis of genetic change in the virus population that may accompany the implementation of new resistance genes to manage rhizomania.
Keyphrases
- genome wide
- genetic diversity
- copy number
- genome wide identification
- risk factors
- escherichia coli
- emergency department
- pseudomonas aeruginosa
- healthcare
- dna methylation
- staphylococcus aureus
- amino acid
- computed tomography
- magnetic resonance imaging
- sars cov
- genome wide analysis
- big data
- south africa
- gene expression
- biofilm formation
- small molecule
- machine learning
- drug induced
- tertiary care
- artificial intelligence