Understanding Plant Pathosystems in Wild Relatives of Cultivated Crop Plants

• Main Author: Fedkenheuer, Michael Gerald
• Other Authors: Plant Pathology, Physiology, and Weed Science
• Format: Others
• Published: Virginia Tech 2018
• Subjects: Glycine max; Glycine soja; Wild Species; Transcriptomics; Oomycete(s)
• Online Access: http://hdl.handle.net/10919/81976

As the global population rises, the demand for food increases which underscores a need for improvement in food security. Disease pressures are a major concern surrounding sustainable agriculture. Static crop populations, containing little to no genetic diversity, are vulnerable to diverse pathogen populations. Wild relatives of crop plants are a reservoir for new disease resistance traits that can be introgressed into cultivated crops. The identification of novel disease resistance is of paramount importance because pathogen co-evolution is not only defeating current resistance genes (R genes) but chemical controls as well. Phytophthora sojae (P. sojae), the causal agent of Phytophthora root and stem rot disease, reduces soybean harvests worldwide. We developed an approach to screen for new R genes that recognize core effectors from P. sojae. We expect R genes identified by these screens to be durable because P. sojae requires core effectors for virulence. We utilized effector-based screening to probe Glycine soja germplasm with core RXLR effectors from P. sojae to search for novel R genes. We developed segregating populations from crosses of P. sojae resistant G. soja germplasm with susceptible G. max cultivar Williams to determine inheritance of potential R genes in germplasm that responded to core effectors. We are using marker assisted breeding to map disease resistance traits in recombinant inbred (RI) lines. To better understand pathosystems, we examined host resistance and susceptibility using bioinformatics. We analyzed the interaction between Arabidopsis thaliana ecotype Col-0 and Hyaloperonospora arabidopsidis isolate Emwa1 using a publicly available RNA time-course experiment. We describe a new algorithm to sort genes into time-point specific clusters using activation and repression parameters. Gene ontology annotations were used to identify defense genes with unique expression profiles, and A. thaliana null mutants for these genes were significantly more susceptible to Emwa1 than wild-type. We plan to use these tools to rapidly identify and guide introgression of durable disease resistance into crop species. === Ph. D.