Genome sequencing and comparison of five Tilletia species to identify candidate genes for the detection of regulated species infecting wheat - Hai D. T. Nguyen; Tahera Sultana; Prasad Kesanakurti; Sarah Hambleton (IMA Fungus)
Abstract Tilletia species cause diseases on grass hosts with some causing bunt diseases on wheat (Triticum). Two of the four species infecting wheat have restricted distributions globally and are subject to quarantine regulations to prevent their spread to new areas. Tilletia indica causes Karnal bunt and is regulated by many countries while the non-regulated T. walkeri is morphologically similar and very closely related phylogenetically, but infects ryegrass (Lolium) and not wheat. Tilletia controversa causes dwarf bunt of wheat (DB) and is also regulated by some countries, while the closely related but non-regulated species, T. caries and T. laevis, both cause common bunt of wheat (CB). Historically, diagnostic methods have relied on cryptic morphology to differentiate these species in subsamples from grain shipments. Of the DNA-based methods published so far, most have focused on sequence variation among tested strains at a single gene locus. To facilitate the development of additional molecular assays for diagnostics, we generated whole genome data for multiple strains of the two regulated wheat pathogens and their closest relatives. Depending on the species, the genomes were assembled into 907 to 4633 scaffolds ranging from 24 Mb to 30 Mb with 7842 to 9952 gene models predicted. Phylogenomic analyses confirmed the placement of Tilletia in the Exobasidiomycetes and showed that T. indica and T. walkeri were in one clade whereas T. controversa, T. caries and T. laevis grouped in a separate clade. Single copy and species-specific genes were identified by orthologous group analysis. Unique species-specific genes were identified and evaluated as suitable markers to differentiate the quarantine and non-quarantine species. After further analyses and manual inspection, primers and probes for the optimum candidate genes were designed and tested in silico, for validation in future wet-lab studies.