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The fungus Fusarium verticillioides can infect maize ears, causing Fusarium ear rot (FER) and contaminating the grain with fumonisins (FUM), which are harmful to humans and animals. Breeding for resistance to FER and FUM and post-harvest sorting of grain are two strategies for reducing FUM in the food system. Kernel and cob tissues have been previously associated with differential FER and FUM. Four recombinant inbred line families from the maize nested associated mapping population were grown and inoculated with F. verticillioides across four environments, and we evaluated the kernels for external and internal infection severity as well as FUM contamination. We also employed publicly available phenotypes on innate ear morphology to explore genetic relationships between ear architecture and resistance to FER and FUM. The four families revealed wide variation in external symptomatology at the phenotypic level. Kernel bulk density under inoculation was an accurate indicator of FUM levels. Genotypes with lower kernel density-under both inoculated and uninoculated conditions-and larger cobs were more susceptible to infection and FUM contamination. Quantitative trait locus (QTL) intervals could be classified as putatively resistance-specific and putatively shared for ear and resistance traits. Both types of QTL mapped in this study had substantial overlap with previously reported loci for resistance to FER and FUM. Ear morphology may be a component of resistance to F. verticillioides infection and FUM accumulation.
Pubmed ID: 30717228
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Software package which performs a variety of genetic analyses including association mapping, diversity estimation and calculating linkage disequilibrium. The association analysis between genotypes and phenotypes can be performed by either a general linear model or a mixed linear model. The general linear model now allows users to analyze complex field designs, environmental interactions, and epistatic interactions. The mixed model is specially designed to handle polygenic effects at multiple levels of relatedness including pedigree information. These new analyses should permit association analysis in a wide range plant and animal species. (entry from Genetic Analysis Software)
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