Uncovering molecular mechanisms of quantitative disease resistance using nested association mapping.

Jesse A. Poland1, Rebecca J. Nelson1, The Maize Diversity Project 1,2,3,4,5,6,7


1Cornell University, Ithaca, NY
2USDA-Agricultural Research Service
3Cold Spring Harbor Laboratory, NY
4University of California-Irvine
5North Carolina State University, Raleigh, NC
6University of Missouri, Columbia, MO
7University of Wisconsin, Madison, WI

Northern Leaf Blight (NLB), caused by Exserohilum turcicum, is an endemic disease affecting maize production worldwide. The most economical and effective method for control of NLB is through the use of genetic resistance in the maize host. Historically both qualitative and quantitative resistance have been important for controlling NLB. Quantitative resistance is important for resistance breeding for crop species in general, as this type of resistance tends to be more durable and broad spectrum. With the goal of uncovering molecular mechanisms conditioning quantitative resistance to NLB, we have begun evaluating the nested association mapping (NAM) population for resistance to NLB. A sub-set of the NAM lines were evaluated in NY during the summer of 2007 for two components of disease: incubation period (number of days until the appearance of disease symptoms) and disease severity. Using this preliminary data, quantitative trait loci (QTL) for NLB resistance have been localized to several genomic locations previously associated with NLB resistance but with greater precision than previous studies. A total of 22 QTL were mapped with a LOD score of 3 or more and 14 of these QTL had a LOD greater than 5. Most QTL map to regions previously shown to associate with NLB resistance but novel QTL were also detected. The largest QTL in the populations was mapped to a 5 cM region in bin 8.06, which is known to carry the resistance gene Htn1. With these populations we were also able to observe allelic series at 8 of the 22 QTL identified. Future analysis with the NAM populations will facilitate higher resolution of QTL and selection of candidate genes which was previously not possible due to the very large regions defined by QTL.

1Cornell University, Ithaca, NY; USDA-Agricultural Research Service; Cold Spring Harbor Laboratory, NY; University of California-Irvine; North Carolina State University, Raleigh, NC; University of Missouri, Columbia, MO; University of Wisconsin, Madison, WI

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Uncovering molecular mechanisms of quantitative disease resistance using nested association mapping
Poland, Jesse A1; Nelson, Rebecca J1; The Maize Diversity Project, 2
1 Dept. of Plant Breeding and Genetics, Cornell University, Ithaca, NY;
2 USDA-Agricultural Research Service; Cold Spring Harbor Laboratory, NY; Cornell University, Ithaca, NY; University of California-Irvine; North Carolina State University, Raleigh, NC; University of Missouri, Columbia, MO; University of Wisconsin, Madison, WI

Northern Leaf Blight (NLB), caused by Exserohilum turcicum, is an endemic disease affecting maize production worldwide. The most economical and effective method for control of NLB is through the use of genetic resistance in the maize host. Historically both qualitative and quantitative resistance have been important for resistance to NLB. Quantitative resistance is important for resistance breeding for crop species in general, as this type of resistance tends to be more durable and broad spectrum. With the goal of uncovering molecular mechanisms conditioning quantitative resistance to NLB, we have begun evaluating the nested association mapping (NAM) population for resistance to NLB. A sub-set of the NAM lines were evaluated in NY during the summer of 2007 for two components of disease: incubation period (number of days until the appearance of disease symptoms) and disease severity. Using this preliminary data, quantitative trait loci (QTL) for NLB resistance have been localized to several genomic locations previously associated with NLB resistance but with greater precision than previous studies. A total of 22 QTL were mapped with a LOD score of 3 or more and 14 of these QTL had a LOD greater than 5. Most QTL map to regions previously shown to associate with NLB resistance but novel QTL were also detected. The largest QTL in the populations was mapped to a 5 cM region in bin 8.06, which is known to carry the resistance gene Htn1. With these populations we were also able to observe allelic series at 8 of the identified QTL. Future analysis with the NAM populations will facilitate higher resolution of QTL and selection of candidate genes which was previously not possible due to the very large regions defined by QTL for disease resistance.