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dc.contributor.authorLopez-Zuniga, Luis O.en
dc.contributor.authorWolters, P.en
dc.contributor.authorDavis, S.en
dc.contributor.authorWeldekidan, T.en
dc.contributor.authorKolkman, J. M.en
dc.contributor.authorNelson, R.en
dc.contributor.authorHooda, K. S.en
dc.contributor.authorRucker, Elizabethen
dc.contributor.authorThomason, Wade E.en
dc.contributor.authorWisser, R.en
dc.contributor.authorBalint-Kurti, P.en
dc.date.accessioned2019-04-10T18:45:26Zen
dc.date.available2019-04-10T18:45:26Zen
dc.date.issued2019-01-09en
dc.identifier.issn21601836en
dc.identifier.urihttp://hdl.handle.net/10919/88885en
dc.description.abstractSouthern Leaf Blight (SLB), Northern Leaf Blight (NLB), and Gray Leaf Spot (GLS) caused by Cochliobolus heterostrophus, Setosphaeria turcica, and Cercospora zeae-maydis respectively, are among the most important diseases of corn worldwide. Previously, moderately high and significantly positive genetic correlations between resistance levels to each of these diseases were identified in a panel of 253 diverse maize inbred lines. The goal of this study was to identify loci underlying disease resistance in some of the most multiple disease resistant (MDR) lines by the creation of chromosome segment substitution line (CSSL) populations in multiple disease susceptible (MDS) backgrounds. Four MDR lines (NC304, NC344, Ki3, NC262) were used as donor parents and two MDS lines (Oh7B, H100) were used as recurrent parents to produce eight BC3F4:5 CSSL populations comprising 1,611 lines in total. Each population was genotyped and assessed for each disease in replicated trials in two environments. Moderate to high heritabilities on an entry mean basis were observed (0.32 to 0.83). Several lines in each population were significantly more resistant than the MDS parental lines for each disease. Multiple quantitative trait loci (QTL) for disease resistance were detected for each disease in most of the populations. Seventeen QTL were associated with variation in resistance to more than one disease (SLB/NLB: 2; SLB/GLS: 7; NLB/GLS: 2 and 6 to all three diseases). For most populations and most disease combinations, significant correlations were observed between disease scores and also between marker effects for each disease. The number of lines that were resistant to more than one disease was significantly higher than would be expected by chance. Using the results from individual QTL analyses, a composite statistic based on Mahalanobis distance (Md) was used to identify joint marker associations with multiple diseases. Across all populations and diseases, 246 markers had significant Md values. However further analysis revealed that most of these associations were due to strong QTL effects on a single disease. Together, these findings reinforce our previous conclusions that loci associated with resistance to different diseases are clustered in the genome more often than would be expected by chance. Nevertheless true MDR loci which have significant effects on more than one disease are still much rarer than loci with single disease effects. © 2019 by the Genetics Society of America.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.publisherGenetics Society of Americaen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectMaize diseaseen
dc.subjectMultiple diseaseen
dc.subjectQTLen
dc.subjectresistanceen
dc.subjectresistanceen
dc.titleUsing maize chromosome segment substitution line populations for the identification of loci associated with multiple disease resistanceen
dc.typeArticle - Refereeden
dc.contributor.departmentSchool of Plant and Environmental Sciencesen
dc.description.notesFunding for the work was provided by USDA-ARS, the Corn Growers’ Association of North Carolina and by NSF grant #1127076 to RJW and PBK. LLZ was supported by a grant from Fulbright Colombia and COLCIENCIAS. We thank Cathy Herring and the staff at Central crops for excellent field support, Shannon Sermons, David Rhyne and Greg Marshall for their technical support. We thank Daniel Gorman, David Bubeck and DuPont-Pioneer for their assistance with field trials in Andrews NC. We thank Jim Holland and Marc Cubeta for their advice and for reviewing the manuscript.en
dc.title.serialG3: Genes, Genomes, Geneticsen
dc.identifier.doihttps://doi.org/10.1534/g3.118.200866en
dc.identifier.volume9en
dc.identifier.issue1en
dc.type.dcmitypeTexten
dc.identifier.pmid30459178en


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Creative Commons Attribution 4.0 International
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