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Theoretical and Applied Genetics

, Volume 128, Issue 3, pp 489–499 | Cite as

Spot form of net blotch resistance in barley is under complex genetic control

  • Xuemin Wang
  • Emma S. Mace
  • Gregory J. Platz
  • Colleen H. Hunt
  • Lee T. Hickey
  • Jerome D. Franckowiak
  • David R. Jordan
Original Paper

Abstract

Key message

Evaluation of resistance to Pyrenophora teres f. maculata in barley breeding populations via association mapping revealed a complex genetic architecture comprising a mixture of major and minor effect genes.

Abstract

In the search for stable resistance to spot form of net blotch (Pyrenophora teres f. maculata, SFNB), association mapping was conducted on four independent barley (Hordeum vulgare L.) breeding populations comprising a total of 898 unique elite breeding lines from the Northern Region Barley Breeding Program in Australia for discovery of quantitative trait loci (QTL) influencing resistance at seedling and adult plant growth stages. A total of 29 significant QTL were validated across multiple breeding populations, with 22 conferring resistance at both seedling and adult plant growth stages. The remaining 7 QTL conferred resistance at either seedling (2 QTL) or adult plant (5 QTL) growth stages only. These 29 QTL represented 24 unique genomic regions, of which five were found to co-locate with previously identified QTL for SFNB. The results indicated that SFNB resistance is controlled by a large number of QTL varying in effect size with large effects QTL on chromosome 7H. A large proportion of the QTL acted in the same direction for both seedling and adult responses, suggesting that phenotypic selection for SFNB resistance performed at either growth stage could achieve adequate levels of resistance. However, the accumulation of specific resistance alleles on several chromosomes must be considered in molecular breeding selection strategies.

Keywords

Quantitative Trait Locus Association Mapping Adult Plant Quantitative Trait Locus Region DArT Marker 
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.

Notes

Acknowledgments

We would like to give thanks to Ms Janet Barsby (DAFFQ), Mr Ryan Fowler (DAFFQ) and Ms Julie McKavanagh (DAFFQ) for technical assistance in the laboratory and field, and to Mr Michael Hassell (DAFFQ) for generating the pedigree diagram of the four breeding populations. We acknowledge funding support from the Grains Research and Development Corporation (GRDC) of Australia.

Conflict of interest

The authors declare they have no conflict of interest.

Supplementary material

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Copyright information

© Her Majesty the Queen in Right of Australia as represented by The State of Queensland 2015

Authors and Affiliations

  • Xuemin Wang
    • 1
  • Emma S. Mace
    • 2
  • Gregory J. Platz
    • 2
  • Colleen H. Hunt
    • 1
    • 2
  • Lee T. Hickey
    • 3
  • Jerome D. Franckowiak
    • 2
    • 4
  • David R. Jordan
    • 1
  1. 1.Queensland Alliance for Agriculture and Food Innovation, Hermitage Research FacilityThe University of QueenslandWarwickAustralia
  2. 2.Department of Agriculture, Fisheries and ForestryHermitage Research FacilityWarwickAustralia
  3. 3.Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandSt LuciaAustralia
  4. 4.Department of Agronomy and Plant GeneticsUniversity of Minnesota Twin CitiesSt PaulUSA

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