Theoretical and Applied Genetics

, Volume 124, Issue 3, pp 543–553 | Cite as

QTL mapping under truncation selection in homozygous lines derived from biparental crosses

  • Albrecht E. MelchingerEmail author
  • Elena Orsini
  • Chris C. Schön
Original Paper


In plant breeding, a large number of progenies that will be discarded later in the breeding process must be phenotyped and marker genotyped for conducting QTL analysis. In many cases, phenotypic preselection of lines could be useful. However, in QTL analyses even moderate preselection can have a significant effect on the power of QTL detection and estimation of effects of the target traits. In this study, we provide exact formulas for quantifying the change of allele frequencies within marker classes, expectations of marker contrasts and the variance of the marker contrasts under truncation selection, for the general case of two QTL affecting the target trait and a correlated trait. We focused on homozygous lines derived at random from biparental crosses. The effects of linkage between the marker and the QTL under selection as well as the effect of selection on a correlated trait can be quantified with the given formulas. Theoretical results clearly show that depending on the magnitude of QTL effects, high selection intensities can lead to a dramatic reduction in power of QTL detection and that approximations based on the infinitesimal model deviate substantially from exact solutions. The presented formulas are valuable for choosing appropriate selection intensity when performing QTL mapping experiments on the data on phenotypically preselected traits and enable the calculation and bias correction of the effects of QTL under selection. Application of our theory to experimental data revealed that selection-induced bias of QTL effects can be successfully corrected.


Quantitative Trait Locus Quantitative Trait Locus Analysis Truncation Selection Quantitative Trait Locus Mapping Marker Contrast 
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 financed by the Deutsche Forschungsgemeinschaft (DFG) research grant SCHO 690/2-1. We are indebted to Dr. Xuefei Mi for his support in preparing the graphics. This paper is dedicated to Prof. Dr. Adolf Martin Steiner on the occasion of his 75th birthday, to whom A.E.M. and C.C.S. owe big gratitude for advice and support in their professional career.

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

122_2011_1727_MOESM1_ESM.doc (601 kb)
Supplementary material (DOC 601 kb)


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Albrecht E. Melchinger
    • 1
    Email author
  • Elena Orsini
    • 1
  • Chris C. Schön
    • 2
  1. 1.Institute of Plant Breeding, Seed Science, and Population GeneticsUniversity of HohenheimStuttgartGermany
  2. 2.Plant Breeding, Center of Life and Food Sciences WeihenstephanTechnische Universität MünchenFreisingGermany

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