Theoretical and Applied Genetics

, Volume 118, Issue 2, pp 347–358 | Cite as

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

  • Alizera Navabi
  • D. E. Mather
  • J. Bernier
  • D. M. Spaner
  • G. N. Atlin
Original Paper


Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to ‘trait-based’ analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to ‘marker-based’ analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.


Quantitative Trait Locus Segregation Distortion Quantitative Trait Locus Effect Quantitative Trait Locus Detection Quantitative Trait Locus Allele 
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.



This research was conducted with financial support from research grants provided by the Canadian International Development Agency, Natural Sciences and Engineering Research Council of Canada, the Alberta Agricultural Research Institute, and the Alberta Crop Industry Development Fund. Genetic simulation experiments were conducted in part by using Perl scripts written by Hai Pham. We thank Hai Pham and Nicholas Tinker for providing access to this unpublished software and we thank Hai Pham for helping with computer programming. We are also grateful to Chris-Carolin Schön for critical review of an earlier version of the manuscript. We are grateful for the insightful suggestions of several anonymous reviewers.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Alizera Navabi
    • 1
    • 2
  • D. E. Mather
    • 3
  • J. Bernier
    • 1
    • 4
  • D. M. Spaner
    • 1
  • G. N. Atlin
    • 5
  1. 1.Department of Agricultural, Food, and Nutritional ScienceUniversity of AlbertaEdmontonCanada
  2. 2.Agriculture and Agri-Food Canada, Department of Plant AgricultureUniversity of GuelphGuelphCanada
  3. 3.Molecular Plant Breeding Cooperative Research Centre and School of Agriculture, Food and WineUniversity of AdelaideGlen OsmondAustralia
  4. 4.IRRI, DAPO 7777Metro ManilaPhilippines
  5. 5.CIMMYTMexico, D.F.Mexico

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