Genome-Based Selection and Characterization of Fusarium circinatum-Specific Sequences

G3 (Bethesda). 2016 Feb 17;6(3):631-9. doi: 10.1534/g3.115.025817.

Abstract

Fusarium circinatum is an important pathogen of pine trees and its management in the commercial forestry environment relies largely on early detection, particularly in seedling nurseries. The fact that the entire genome of this pathogen is available opens new avenues for the development of diagnostic tools for this fungus. In this study we identified open reading frames (ORFs) unique to F. circinatum and determined that they were specific to the pathogen. The ORF identification process involved bioinformatics-based screening of all the putative F. circinatum ORFs against public databases. This was followed by functional characterization of ORFs found to be unique to F. circinatum. We used PCR- and hybridization-based approaches to confirm the presence of selected unique genes in different strains of F. circinatum and their absence from other Fusarium species for which genome sequence data are not yet available. These included species that are closely related to F. circinatum as well as those that are commonly encountered in the forestry environment. Thirty-six ORFs were identified as potentially unique to F. circinatum. Nineteen of these encode proteins with known domains while the other 17 encode proteins of unknown function. The results of our PCR analyses and hybridization assays showed that three of the selected genes were present in all of the strains of F. circinatum tested and absent from the other Fusarium species screened. These data thus indicate that the selected genes are common and unique to F. circinatum. These genes thus could be good candidates for use in rapid, in-the-field diagnostic assays specific to F. circinatum. Our study further demonstrates how genome sequence information can be mined for the identification of new diagnostic markers for the detection of plant pathogens.

Keywords: diagnostic candidates; genes; pitch canker; unique.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Evolution, Molecular
  • Fusarium / genetics*
  • Genes, Fungal
  • Genome, Fungal*
  • Genomics* / methods
  • Open Reading Frames
  • Selection, Genetic*