GENOME SEQUENCE-BASED STRATEGIES FOR DETECTION & IDENTIFICATION OF PLANT PATHOGENIC PHYTOPLASMAS & SPIROPLASMAS, & VASCULAR WALLED BACTERIA
Location: Molecular Plant Pathology
Project Number: 1245-22000-282-00
Start Date: Feb 26, 2012
End Date: Feb 25, 2017
Objective 1: Identify molecular biomarkers useful for detection and identification of phytoplasmas and plant pathogenic spiroplasmas at clade, group, subgroup, species, pathotype, and strain levels.
Objective 2: Expand and refine the current gene-based phytoplasma classification system.
Objective 3: Establish a framework toward DNA barcoding of plant pathogenic mollicutes, a system for multilocus genotyping, strain description, and eventual formal molecular taxonomy of spiroplasmas and phytoplasmas.
The goal of this project is to discover and utilize new knowledge to devise and develop new, improved technologies to detect, identify, and classify phytoplasmas and spiroplasmas (mollicutes) that cause economically important plant diseases. We will identify highly conserved genes, moderately sequence-variable genes, and rapidly evolving genes, across phylogenetically divergent lineages. Small genomes, and evolutionary loss of genes and metabolic functions, make mollicutes ideal models for comparative genomics. Comparative genomics will elucidate genotypic events in evolutionary emergence of the phytoplasma clade, and will help establish molecular markers for genus-level identification and criteria for formal genus Phytoplasma taxonomy. Established species of spiroplasmas will serve as models for assessing inter- and intra-species sequence variability and for delineating gene sets to be evaluated as a conceptual framework to distinguish putative species and genera of phytoplasmas. Phytoplasmal genetic SNPs and sequences of rapidly evolving genes, including lineage-specific pathogenicity genes, will provide unique molecular biomarkers for improved detection and identification. A previously developed online program for computer-assisted phytoplasma classification will be expanded to accommodate automated analysis of diverse functional classes of genes. Subsets of multiple gene sequences will be assembled to configure “constellations” of diverse molecular biomarkers for use in constructing DNA barcodes for phytoplasma identification, for detection and classification of new phytoplasmas in emerging diseases, and for use as molecular descriptors in a formal Phytoplasma spp. taxonomy. The new knowledge gained and the technologies and tools devised will advance fundamental science, strengthen applied research, enhance disease management, and improve implementation of quarantine regulations worldwide.