QTL mapping under truncation selection in homozygous lines derived from biparental crosses
- 291 Downloads
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.
KeywordsQuantitative Trait Locus Quantitative Trait Locus Analysis Truncation Selection Quantitative Trait Locus Mapping Marker Contrast
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.
- Cochran W (1951) Improvement by means of selection. In: Proceedings of the second Berkeley symposium on mathematical statistics and probability, vol 8950, pp 449–470Google Scholar
- Deuflhard P (2004) Newton methods for nonlinear problems. Affine invariance and adaptive algorithms. Springer series in computational mathematics, vol 35. Springer, BerlinGoogle Scholar
- Falconer D (1989) Introduction to quantitative genetics, 3rd edn. Longman Scientific & Technical, EnglandGoogle Scholar
- Foody GM, Warner TA, Nellis MD (2009) The SAGE handbook of remote sensing. Sage Publications Ltd, London, pp 105–110; 297–307Google Scholar
- Graybill F (1976) Theory and application of the linear model, 5th edn. Duxbury Press, CaliforniaGoogle Scholar
- Kendall M, Stuart A (1979) The advanced theory of statistics. Inference and relationship, vol 2, 4th edn. Butler and Tanner LTD, Frome and LondonGoogle Scholar
- Martin M, Miedaner T, Dhillon BS, Ufermann U, Kessel B, Ouzunova M, Schipprack W, Melchinger AE (2011) Colocalization of QTL for Giberella ear rot resistance and low mycotoxin contamination in early European flint maize. Crop Sci 51:1935–1945Google Scholar
- Mood MA, Graybill AF, Boes DC (1974) Introduction to the theory of statistics, 3th edn. MacGraw-Hill Book Company, SingaporeGoogle Scholar
- Utz H, Melchinger A (1996) PLABQTL: a program for composite interval mapping of QTL. J Quant Trait Loci 2:1–5Google Scholar