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Theoretical and Applied Genetics

, Volume 113, Issue 4, pp 753–766 | Cite as

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

  • X. Q. Huang
  • S. Cloutier
  • L. Lycar
  • N. Radovanovic
  • D. G. Humphreys
  • J. S. Noll
  • D. J. Somers
  • P. D. Brown
Original Paper

Abstract

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F1-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.

Keywords

Plant Height Doubled Haploid Agronomic Trait Doubled Haploid Line Composite Interval Mapping 
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 thank the breeding teams at Winnipeg and Brandon for the field experiments and evaluations, Elsa Reimer for excellent assistance in genotyping and Sheila Woods for statistical analysis advice. Review of the manuscript and useful comments provided by Andrzej Walichnowski, and Drs Curt McCartney and David De Koeyer are greatly acknowledged. X. Q. Huang received a visiting fellowship from the National Science and Engineering Research Council of Canada (NSERC). This research was supported in part by an NSERC post-graduate scholarship to N. Radovanovic. This publication is Agriculture and Agri-Food Canada contribution no. 1921.

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • X. Q. Huang
    • 1
  • S. Cloutier
    • 1
  • L. Lycar
    • 1
  • N. Radovanovic
    • 1
  • D. G. Humphreys
    • 1
  • J. S. Noll
    • 1
  • D. J. Somers
    • 1
  • P. D. Brown
    • 1
  1. 1.Cereal Research CentreAgriculture and Agri-Food CanadaWinnipegCanada

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