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Study of genetic distances between cattle breeds of Central Europe

Author

Listed:
  • J. Čítek

    (Department of Animal Breeding, University of South Bohemia, České Budějovice, Czech Republic)

  • L. Panicke

    (Research Institute for the Biology of Farm Animals, Dummerstorf, Germany)

  • V. Řehout

    (Department of Animal Breeding, University of South Bohemia, České Budějovice, Czech Republic)

  • H. Procházková

    (Department of Animal Breeding, University of South Bohemia, České Budějovice, Czech Republic)

Abstract

Genetic distances were studied among Czech Red cattle, German Red, Czech Pied, Polish Red, Czech Black and White, and German Black and White cattle. DA genetic distances were calculated, and trees were constructed using the neighbour-joining method. Evaluating the genetic distances by microsatellites, the lowest value was between Czech and German Black and White breeds. A surprisingly high value was found between Czech and German Red breeds, and the highest values between German Red breed and both German and Czech Black and White populations came up to expectations. In the phylogenetic tree made using microsatellites, the German and Polish Red breeds clustered, but Czech Red breed was not joined with them. The other cluster was obtained for Czech Black and White and German Black and White. The tree made of protein markers differed slightly. Because the populations of Czech and German Red breeds are small and also because of organizational issues, the common protection of Central-European red populations and breeding them as a gene pool are recommended.

Suggested Citation

  • J. Čítek & L. Panicke & V. Řehout & H. Procházková, 2006. "Study of genetic distances between cattle breeds of Central Europe," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 51(10), pages 429-436.
    • Handle: RePEc:caa:jnlcjs:v:51:y:2006:i:10:id:3961-cjas
    DOI: 10.17221/3961-CJAS
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    References listed on IDEAS

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    1. J. Kučerová & A. Matějíček & O.M. Jandurová & P. Sørensen & E. Němcová & M. Štípková & T. Kott & J. Bouška & J. Frelich, 2006. "Milk protein genes CSN1S1, CSN2, CSN3, LGB and their relation to genetic values of milk production parameters in Czech Fleckvieh," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 51(6), pages 241-247.
    2. G. Freyer & N. Vukasinovic, 2005. "Comparison of granddaughter design and general pedigree design analysis of QTL in dairy cattle: a simulation study," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 50(12), pages 545-552.
    3. V. Czerneková & T. Kott & G. Dudková & Z. Sztankóová & J. Soldát, 2006. "Genetic diversity between seven Central European cattle breeds as revealed by microsatellite analysis," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 51(1), pages 1-7.
    4. A. Maj & N. Strzałkowska & K. Słoniewski & J. Krzyżewski & J. Oprządek & L. Zwierzchowski, 2004. "Single nucleotide polymorphism (SNP) in the 5'-noncoding region of the bovine growth hormone receptor gene and its association with dairy production traits in Polish Black-and-White cattle," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 49(10), pages 419-429.
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    Cited by:

    1. A. Stachurska & A. Nogaj & A. Brodacki & J. Nogaj & J. Batkowska, 2014. "Genetic distances between horse breeds in Poland estimated according to blood protein polymorphism," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 59(6), pages 257-267.
    2. I. Manga & J. Dvořák, 2010. "TaqMan allelic discrimination assay for A1 and A2 alleles of the bovine CSN2 gene," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 55(8), pages 307-312.
    3. J. Stevanovic & Z. Stanimirovic & V. Dimitrijevic & M. Maletic, 2010. "Evaluation of 11 microsatellite loci for their use in paternity testing in Yugoslav Pied cattle (YU Simmental cattle)," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 55(6), pages 221-226.

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