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Volume 54, issue 4
Arch. Anim. Breed., 54, 348–359, 2011
https://doi.org/10.5194/aab-54-348-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Arch. Anim. Breed., 54, 348–359, 2011
https://doi.org/10.5194/aab-54-348-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Oct 2011

10 Oct 2011

QTL explaining variation in production traits and udder health in the Danish Holstein population

H. Thomsen1, J. R. Thomasen2, B. Guldbrandtsen1, and M. S. Lund1 H. Thomsen et al.
  • 1Department of Genetics and Biotechnology, University of Aarhus, P.O. Box 50, Tjele, Denmark
  • 2Viking Genetics, Ebeltoftvej 16, Assentoft, Randers, Denmark

Abstract. The main objective was to locate QTL and estimate the proportion of total genetic variance attributable to quantitative trait loci (QTL) for production index traits and the udder health index identified on six Bos taurus autosomes in the Danish Holstein dairy cattle population.

Data were obtained from a granddaughter design of 20 sire families with a total of 1 869 progeny tested sons. The number of sons per grandsire ranged from 20 to 284, with an average family size of 93.5. Indexes of the estimated breeding values were obtained for the milk production traits and for the udder health index from the Danish Agricultural Advisory Service database.

A random-QTL model was applied to incorporate marker information into parameter estimation for each single QTL. The procedure allowed us to detect new QTL on BTA3, BTA16 and BTA28 and to estimate the proportion of total genetic variance attributed to different QTL on a total of six Bos taurus autosomes for the udder health index and yield index traits in the Danish Holstein population. Variance estimates vary between 2 to 58 % of the total variance for different QTL and seem to explain a substantial part of the variance at certain positions of the cattle genome.

The results are discussed against the background of the failure of marker-assisted selection (MAS) and the recent availability of large panels of single nucleotide polymorphisms (SNPs) that have improved the search for mutations underlying variation in complex traits resulting in modern genomic selection.

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