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Maize significantly contributes to food and fuel production. Yields can be reduced due to foliar diseases, which reduce photosynthetic leaf area. The bacterial foliar disease Goss's wilt (caused byClavibacter nebraskensis) can cause significant yield losses in susceptible maize varieties.C. nebraskensiscan infect leaves through wounds and colonize the vascular tissue of the leaf. We present a protocol that replicates this process with the use of a “clapper” with pins on one end to create wounds and a sponge soaked in inoculum on the other end, which allows for efficient field inoculations of maize leaves. Disease severity is then rated on a percentage scale multiple times over the season to generate an area under disease progress curve (AUDPC). Genetic host resistance is one of the most effective forms of foliar disease control in maize, as there are few effective forms of chemical control for bacterial diseases that affect maize. Screening for resistance in diverse germplasm, or for fine mapping a specific resistance gene, requires inoculating large populations in the field for obtaining phenotypic data. Our high-throughput protocol allows for large-scale disease evaluations and is useful for finding forms of genetic resistance or to understand plant–pathogen interactions of bacterial foliar pathogens.
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Identification of loci conferring resistance to 4 foliar diseases of maize
Abstract Foliar diseases of maize are among the most important diseases of maize worldwide. This study focused on 4 major foliar diseases of maize: Goss's wilt, gray leaf spot, northern corn leaf blight, and southern corn leaf blight. QTL mapping for resistance to Goss’s wilt was conducted in 4 disease resistance introgression line populations with Oh7B as the common recurrent parent and Ki3, NC262, NC304, and NC344 as recurrent donor parents. Mapping results for Goss’s wilt resistance were combined with previous studies for gray leaf spot, northern corn leaf blight, and southern corn leaf blight resistance in the same 4 populations. We conducted (1) individual linkage mapping analysis to identify QTL specific to each disease and population; (2) Mahalanobis distance analysis to identify putative multiple disease resistance regions for each population; and 3) joint linkage mapping to identify QTL across the 4 populations for each disease. We identified 3 lines that were resistant to all 4 diseases. We mapped 13 Goss’s wilt QTLs in the individual populations and an additional 6 using joint linkage mapping. All Goss’s wilt QTL had small effects, confirming that resistance to Goss’s wilt is highly quantitative. We report several potentially important chromosomal bins associated with multiple disease resistance including 1.02, 1.03, 3.04, 4.06, 4.08, and 9.03. Together, these findings indicate that disease QTL distribution is not random and that there are locations in the genome that confer resistance to multiple diseases. Furthermore, resistance to bacterial and fungal diseases is not entirely distinct, and we identified lines resistant to both fungi and bacteria, as well as loci that confer resistance to both bacterial and fungal diseases.
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- Award ID(s):
- 2154872
- PAR ID:
- 10513984
- Editor(s):
- McIntyre, L
- Publisher / Repository:
- Genetics Society of America
- Date Published:
- Journal Name:
- G3: Genes, Genomes, Genetics
- Volume:
- 14
- Issue:
- 2
- ISSN:
- 2160-1836
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/g3journal/jkad275
