Degree

Doctor of Philosophy (PhD)

Department

Plant, Environmental, and Soil Sciences

Document Type

Dissertation

Abstract

Bacterial leaf streak (BLS) and black chaff, caused by Xanthomonas translucens pv. undulosa (Xtu), can be a very destructive disease of wheat, especially in the warmer, wetter areas of the Southeastern U.S. Yield losses of up to 40 percent have been recorded in some cases in southern wheat growing regions. With no effective agronomic or chemical method of disease control, identification of genetic resistance is seen as a promising solution. Three soft red winter wheat populations (GAWN, ARK-SNP, and AGS 2060- AGS 2035 DH) representative of soft red winter wheat germplasm in the southeastern U.S. developed by the LSU AgCenter wheat breeding program and the “SunGrains” consortium were used for this study. The main objective of this study was to screen wheat germplasm for resistance to bacterial streak and identify significant single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with resistance to BLS.

Ratings were recorded for leaf and head infection on a percentage (1-100) scale, and then plants were rated based on the overall visualization of the damage on a 1-10 scale (1 being no symptom to 10 being dead). Significant analysis of variance (ANOVA) and Pearson’s Correlation matrices for the observed traits in multiple environments indicate promising phenotypic results. Initial association mapping and biparental quantitative trait locus (QTL) mapping using the 9K and 90K SNP array genotypic data showed 62, 27, and 9 SNPs significantly contributing to BLS resistance across all traits and environments for each of our three diverse populations, thus confirming that this is indeed a complex, quantitative trait. A reduced SNP set of 34 unique markers was constructed to identify significant and stable sources that could be used for increasing resistance to Xtu in wheat. DNA markers identified in this study can be used in MAS (marker assisted selection) for BLS resistance in wheat breeding programs and could be integrated as fixed-effect variables for the development of a robust GS (genomic selection) model.

Date

11-2-2022

Committee Chair

Harrison, Stephen A.

Available for download on Saturday, December 16, 2023

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