Journal of Applied Genetics

, Volume 54, Issue 1, pp 49–60 | Cite as

Modelling QTL effect on BTA06 using random regression test day models

  • T. Suchocki
  • J. Szyda
  • Q. Zhang
Animal Genetics • Original Paper


In statistical models, a quantitative trait locus (QTL) effect has been incorporated either as a fixed or as a random term, but, up to now, it has been mainly considered as a time-independent variable. However, for traits recorded repeatedly, it is very interesting to investigate the variation of QTL over time. The major goal of this study was to estimate the position and effect of QTL for milk, fat, protein yields and for somatic cell score based on test day records, while testing whether the effects are constant or variable throughout lactation. The analysed data consisted of 23 paternal half-sib families (716 daughters of 23 sires) of Chinese Holstein-Friesian cattle genotyped at 14 microsatellites located in the area of the casein loci on BTA6. A sequence of three models was used: (i) a lactation model, (ii) a random regression model with a QTL constant in time and (iii) a random regression model with a QTL variable in time. The results showed that, for each production trait, at least one significant QTL exists. For milk and protein yields, the QTL effect was variable in time, while for fat yield, each of the three models resulted in a significant QTL effect. When a QTL is incorporated into a model as a constant over time, its effect is averaged over lactation stages and may, thereby, be difficult or even impossible to be detected. Our results showed that, in such a situation, only a longitudinal model is able to identify loci significantly influencing trait variation.


Dairy cattle QTL Legendre polynomials Longitudinal data 

Supplementary material

13353_2012_114_MOESM1_ESM.docx (470 kb)
ESM 1 (DOCX 470 kb)


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Copyright information

© Institute of Plant Genetics, Polish Academy of Sciences, Poznan 2012

Authors and Affiliations

  1. 1.Department of GeneticsWrocław University of Environmental and Life SciencesWrocławPoland
  2. 2.College of Animal Science and TechnologyChina Agricultural UniversityBeijingPeople’s Republic of China

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