ARS | Publication request: Utilization of Genomic Variations Among Xylella fastidiosa Strains for Improved Diagnostic Design

Submitted to: American Phytopathology Society
Publication Type: Abstract Only
Publication Acceptance Date: March 15, 2007
Publication Date: July 28, 2007
Citation: Lin, H., Doddapaneni, H., Yao, J., Civerolo, E.L. 2007. Utilization of Genomic Variations Among Xylella fastidiosa Strains for Improved Diagnostic Design. American Phytopathology Society. 97(7):64

Technical Abstract: The Gram-negative, xylem-limited phytopathogenic bacterium Xylella fastidiosa causes economically important diseases in grapevine, citrus and many other plant species. Our recent whole genome comparative analysis of the four sequenced strains has identified genomic variation among these strains. There are 1,579 genes and 194 non-coding homologous sequences present in the genomes of the four published Xylella fastidiosa strains, representing 76.2% conservation of the sequenced genome. Further, the analysis identified 12,754 potential SNPs in coding sequences and 20,779 SNPs in non-coding regions. In addition, tandem repeat, frame-shift mutations and unique gene clusters were identified and incorporate into citrus/grape disease database (CDD, http://cropdisease.ars.usda.gov/CVC_index.htm). Based on these results, we have developed a high-resolution Xf diagnostic system using spotted arrays as the platform with in silico designed 60-mer probes for species (213 oligos) as well as strain differentiations (9a5c, 231 oligos; Ann1, 134; Dixon, 62 and Temecula-1, 98). Validation tests at 16 loci for strain specific SNPs using 18 strains from grape, citrus, almond and oleander plants showed tight linkages of SNP genotype to the hosts from which the strains were derived. Testing of INDELs based single locus multi-strain diagnosis system is in progress. Our goal is to utilize DNA variations for developing, highly target specific multiplex real-time PCR assays, characterization of host association, pathogen interactions based on SNP surveys, and microarray-based similarity index profiles for strain characterization.