The Genetic Architecture Of Quantitative Disease Resistance In Maize

Poland, Jesse

The Genetic Architecture Of Quantitative Disease Resistance In Maize

Abstract

Several large scale quantitative genetic studies were conducted to better understand the genetic basis for quantitative disease resistance (QDR) in plants. The focus of these studies was the economically important disease of maize (Zea mays L. ssp. mays), northern leaf blight (NLB, caused by Setosphaeria turcica L. anamorph Exserohilum turcicum). The maize nested association mapping (NAM) population, a reference design population consisting of 4,630 recombinant inbred lines, was evaluated over three environments for quantitative resistance to NLB, giving highly heritable resistance phenotypes. Over 200 resistance alleles at 30 different quantitative trait loci (QTL) for disease resistance were identified. Genome-wide nested association mapping for NLB resistance identified genes at six of the QTL that have been associated with disease resistance including three receptor-like kinases, two ethylene response factors, and one Mlo-like gene. Further insight on QDR, with a focus on multiple disease resistance (MDR), was gained by jointly analyzing independent data on NAM for resistance to southern leaf blight (SLB), gray leaf spot (GLS) and NLB. To examine the possibility of MDR genes, the estimated allele effects from each founder inbred were compared at loci were QTL for two or more diseases co-localized. At seven loci, positively correlated allele effects provided evidence for MDR genes. Analysis of the NAM population suggested that resistance to the three diseases studied here is largely due to the accumulation of disease-specific genes and, to a limited extent, pleiotropic genes that condition MDR. A final study was conducted to determine the effect of variability in visual disease rating on mapping disease QTL by assessing the effects of scorer variability and rating scales on mapping QTL for NLB in a single recombinant inbred line population from NAM. Stepwise general linear model selection (GLM) and inclusive composite interval mapping (ICIM) were used for QTL mapping. For both GLM and ICIM the same QTL were largely found across scorers, though some QTL were only identified by some scorers. Strikingly, the magnitudes of estimated allele effects from different scorers at identified QRL were drastically different, sometime by as much as three fold. The studies conducted here advance the understanding of QDR in plants and lay groundwork for identifying the genes responsible for resistance to NLB in maize. A greater understanding of QDR will assist in the development of durable resistant crop cultivars, improving food security and safety.

Date Issued

2010-04-09T20:22:39Z

Types

dissertation or thesis