Theoretical and Applied Genetics

, Volume 114, Issue 7, pp 1229–1238 | Cite as

Mapping QTLs contributing to Ustilago maydis resistance in specific plant tissues of maize

  • Andrew M. Baumgarten
  • Jayanti Suresh
  • Georgiana May
  • Ronald L. Phillips
Original Paper
First Online:
Received:
Accepted:

Abstract

Quantitative trait loci (QTL) contributing to the frequency and severity of Ustilago maydis infection in the leaf, ear, stalk, and tassel of maize plants were mapped using an A188 × CMV3 and W23 × CMV3 recombinant inbred (RI) populations. QTLs mapped to genetic bins 2.04 and 9.04–9.05 of the maize genome contributed strongly (R 2 = 18–28%) to variation in the frequency and severity of U. maydis infection over the entire plant in both populations and within the majority of environments. QTLs mapped to bins 3.05, 3.08, and 8.00 in the A188 × CMV3 population and bin 4.05 in both populations significantly contributed to the frequency or severity of infection in only the tassel tissue. QTLs mapped to bin 1.07 in the A188 × CMV3 population and bin 7.00 in the W23 × CMV3 population contributed to U. maydis resistance in only the ear tissue. Interestingly, the CMV3 allele of the QTL mapped to bin 1.10 in the A188 × CMV3 population significantly contributed to U. maydis susceptibility in the ear and stalk but significantly increased resistance in the tassel tissue. Digenic epistatic interactions between the QTL mapped to bin 5.08 and four distinct QTLs significantly contributed to the frequency and severity of infection over the entire plant and within the tassel tissue of the A188 × CMV3 population. Several QTLs detected in this study mapped to regions of the maize genome containing previously mapped U. maydis resistance QTLs and genes involved in plant disease resistance.

Keywords

Quantitative Trait Locus Recombinant Inbred Line Epistatic Interaction Recombinant Inbred Entire Plant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

The authors would like to acknowledge the help of both the Phillips and May lab in pollinations and scoring U. maydis infection. This project was supported through a NSF Biocomplexity Grant (DMS-0083468 to G. May), a graduate research grant given to Andrew Baumgarten from the University of Minnesota Center for Community Genetics, and support to Ron Phillips from MN Agricultural Experiment Station. Andrew Baumgarten’s work on this project was supported by graduate research assistantship from the Department of Agronomy and Plant Genetics, a fellowship from the University of Minnesota Plant Molecular Genetics Institute, and a University of Minnesota Doctoral Dissertation Fellowship. The authors would specifically like to thank Andy Dosdall for his efforts on this project.

Supplementary material

122_2007_513_MOESM1_ESM.doc (126 kb)
122_2007_513_MOESM2_ESM.doc (117 kb)

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Andrew M. Baumgarten
    • 1
    • 4
  • Jayanti Suresh
    • 2
  • Georgiana May
    • 3
  • Ronald L. Phillips
    • 2
  1. 1.Department of Plant Biological SciencesUniversity of MinnesotaSt PaulUSA
  2. 2.Department of Agronomy and Plant GeneticsUniversity of MinnesotaSt PaulUSA
  3. 3.Department of Ecology, Evolution and BehaviorUniversity of MinnesotaSt PaulUSA
  4. 4.Pioneer Hi-bred International, Inc.JohnstonUSA

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