Theoretical and Applied Genetics

, Volume 124, Issue 7, pp 1339–1350 | Cite as

Conditional QTL underlying resistance to late blight in a diploid potato population

  • Jingcai Li
  • Hannele Lindqvist-Kreuze
  • Zhendong Tian
  • Jun Liu
  • Botao Song
  • Juan Landeo
  • Leticia Portal
  • Manuel Gastelo
  • Julio Frisancho
  • Laura Sanchez
  • Dennis Meijer
  • Conghua Xie
  • Merideth Bonierbale
Original Paper
First Online:
Received:
Accepted:

Abstract

A large number of quantitative trait loci (QTL) for resistance to late blight of potato have been reported with a “conventional” method in which each phenotypic trait reflects the cumulative genetic effects for the duration of the disease process. However, as genes controlling response to disease may have unique contributions with specific temporal features, it is important to consider the phenotype as dynamic. Here, using the net genetic effects evidenced at consecutive time points during disease development, we report the first conditional mapping of QTL underlying late blight resistance in potato under five environments in Peru. Six conditional QTL were mapped, one each on chromosome 2, 7 and 12 and three on chromosome 9. These QTL represent distinct contributions to the phenotypic variation at different stages of disease development. By comparison, when conventional mapping was conducted, only one QTL was detected on chromosome 9. This QTL was the same as one of the conditional QTL. The results imply that conditional QTL reflect genes that function at particular stages during the host–pathogen interaction. The dynamics revealed by conditional QTL mapping could contribute to the understanding of the molecular mechanism of late blight resistance and these QTL could be used to target genes for marker development or manipulation to improve resistance.

Keywords

Quantitative Trait Locus Late Blight Quantitative Trait Locus Analysis Quantitative Trait Locus Mapping Late Blight Resistance 
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

This work was partially funded by the Natural Science Foundation of Hubei Province of China (2010CDA102), the “948” Project from the Ministry of Agriculture of China [2006-G12(B)]and the Earmarked Fund for Modern Agro-industry Technology Research System of China(nycytx-15). Research at CIP was funded by Technical Coordination Secretariat of the Consultative Group on International Agricultural Research (Peru) and United States Agency for International Development (USAID). We are thankful to Luis Rivera for running SSR marker analysis at CIP.

Supplementary material

122_2012_1791_MOESM1_ESM.xls (36 kb)
Supplementary material 1 (XLS 37 kb)

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Jingcai Li
    • 1
  • Hannele Lindqvist-Kreuze
    • 2
  • Zhendong Tian
    • 1
  • Jun Liu
    • 1
  • Botao Song
    • 1
  • Juan Landeo
    • 2
  • Leticia Portal
    • 2
  • Manuel Gastelo
    • 2
  • Julio Frisancho
    • 2
  • Laura Sanchez
    • 2
  • Dennis Meijer
    • 2
  • Conghua Xie
    • 1
  • Merideth Bonierbale
    • 2
  1. 1.Key Laboratory of Horticultural Plant Biology (Huazhong Agricultural University), Ministry of Education, National Center for Vegetable Improvement (Central China), Potato Engineering and Technology Research Center of Hubei ProvinceHuazhong Agricultural UniversityWuhanPeople’s Republic of China
  2. 2.International Potato CenterLimaPeru

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