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Theoretical and Applied Genetics

, Volume 110, Issue 3, pp 561–566 | Cite as

Statistical tests for QTL and QTL-by-environment effects in segregating populations derived from line crosses

  • H. P. PiephoEmail author
Original Paper

Abstract

Quantitative trait locus (QTL) studies in plants frequently employ phenotypic data on a population of lines (doubled haploid lines, recombinant inbred lines, etc.) tested in multiple environments. An important feature of such data is the genetic correlation among observations on the same genotype in different environments. Detection of QTL-by-environment interaction requires tests which take this correlation into account. In this article, a comparison was made of the properties of several such tests by means of simulation. The results indicate that a split-plot analysis of variance (anova), being an approximate method, tends to be too liberal under departures from the Huynh-Feldt condition. A standard two-way anova, which ignores genetic correlation, yields inappropriate tests and should be avoided. In contrast, mixed model approaches as well as univariate and multivariate repeated-measures anova yield valid results. This supports the use of a flexible mixed model framework in more complex settings, which are difficult to tackle by repeated-measures anova.

Keywords

Quantitative Trait Locus Genetic Correlation Mixed Model Analysis Mixed Model Approach Unstructured Model 
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

Acknowledgements

I thank Andreas Büchse for helpful comments on earlier versions of this manuscript.

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Bioinformatics UnitUniversität HohenheimStuttgartGermany

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