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Title:Identification and characterization of Fusarium graminearum pathogenesis genes and determination of aggressiveness
Author(s):Salazar, Melissa Marie
Advisor(s):Mideros, Santiago
Contributor(s):Bollero, German; Kolb, Frederic; Butts-Wilmsmeyer, Carolyn
Department / Program:Crop Sciences
Discipline:Crop Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Fusarium, graminearum, Fusarium graminearum, FHB, Fusarium head blight, aggressiveness, pathogenesis, acuminatum, armeniacum
Abstract:Fusarium graminearum, the causal agent of Fusarium head blight of wheat, is a devastating pathogen that causes yield and quality losses to its host. F. graminearum produces mycotoxins in the grain that cause reduced milling and baking qualities, granary rejection, and livestock feed refusal. Research has been conducted to identify genes associated with deoxynivalenol, the most important mycotoxin produced by F. graminearum, yet little is known about other pathogenesis compounds or pathways used by the pathogen to infect wheat. To identify essential fungal pathogenesis genes and determine whether host resistance impacts aggressiveness of a given isolate, a paired strategy of isolate and transcriptome characterization of naturally infected wheat lines was implemented. In the summer of 2016, naturally infected spikelets that symptomatically resembled Fusarium head blight were collected from soft red winter wheat with varying levels of resistance. Collected Fusarium isolates were surface sterilized, grown on potato dextrose agar with rifamycin for six days, and single spored. Of the original collected isolates, twelve were utilized as a representative sample to ascertain aggressiveness. Species identification was completed for the twelve isolates by sequencing the translation elongation factor 1-alpha gene (EF1-α) using EF1/EF2 primers. DNA was trimmed and blasted for species similarities using the Fusarium ID database. Of the twelve isolates, seven identified as F. graminearum (Schwabe), three as F. armeniacum, and two were non-determinant. Aggressiveness was categorized through the utilization of two field assays, one greenhouse assay, mycotoxin assays, and a spore quantification assay. Pathogenesis assays were conducted with the representative Fusarium isolates and a negative control. During anthesis, isolates were inoculated in the center spikelet of wheat heads from two cultivars and were replicated per assay. Fungal aggressiveness was determined through disease severity with information taken at 14, 21, and 28 days post inoculation with area under the disease progress curves calculated from severity data. After threshing inoculated heads for each aggressiveness assay, Fusarium damaged kernels were collected, processed, and measured for mycotoxin contamination with Reveal Q+ for DON. Fusarium isolates caused varying levels of infection on inoculated soft red winter wheat. Disease severity differed based on cultivar but was higher on highly susceptible cultivars. Aggressiveness varied among the isolates by origin of collection and level of host resistance from which the isolate was collected from. Spore quantification gave little indication into each isolate’s potential aggressiveness upon inoculation. Currently, aggressiveness is defined as a quantifiable amount of disease caused by a pathogen. To date, there is no single index measurement that syndicates the individual measurements of aggressiveness. The goal of this research was to combine disease severity translated into area under the disease progress curve, Fusarium damaged kernels, and mycotoxin quantification through deoxynivalenol into a single index and quantifiable measurement of aggressiveness. A principal component analysis was conducted on the collective aggressiveness traits from each assay to create a multivariate description of isolate aggressiveness. This index was then employed in a cluster analysis to classify isolates, as described by origin of collection and level of host resistance from which each isolate was collected, into clusters based on the index value.
Issue Date:2019-04-22
Rights Information:Copyright 2019 Melissa Salazar
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05

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