Czech J. Anim. Sci., 2012, 57(4):151-159 | DOI: 10.17221/5890-CJAS

Single-step prediction of genomic breeding value in a small dairy cattle population with strong import of foreign genes

J. Přibyl1, J. Haman1, T. Kott1, J. Přibylová1, M. Šimečková1, L. Vostrý1, L. Zavadilová1, V. Čermák2, Z. Růžička2, J. Šplíchal2, M. Verner2, J. Motyčka3, L. Vondrášek3
1 Institute of Animal Science, Prague-Uhříněves, Czech Republic
2 Czech Moravian Breeding Corporation, Prague, Czech Republic
3 Holstein Cattle Breeders Association of the Czech Republic, Prague, Czech Republic

The breeding value (EBV) of Holstein cattle milk performance from the first lactation was evaluated using a regular Animal Model or by Single-Step Prediction of the genomic breeding value (GEBV). A total of 838 bulls were genotyped using the Illumina BovineSNP50 Beadchip V2. Two overlapping sets of milk performances were evaluated: calving years 1991-2004, with 729 341 lactations and 1 394 487 animals in the pedigree and calving years 1996-2009, with 808 436 lactations and 1 487 608 animals in the pedigree. The older data set included 526 genotyped bulls, in which the daughters' milk performance was known for 210 individuals. All of the genotyped animals were included in the newer data set. Of the young genotyped bulls from the older set, 279 had more than 50 daughters with performance records in the newer set. Genomic relationship matrices (G) were constructed from the allele frequencies of the current genotyped population or by assuming a constant value of 0.5 for all loci. Using current allele frequencies, the correlation of G with the pedigree relationship (A) was 0.74, while it was 0.77 when the constant value was used. G was blended with A with weights of 80 or 99%. The average EBV of the genotyped bulls exceeded the mean EBV of the entire population by 3 SD. Although the number of reference bulls was small, genotyping resulted in an increase of approximately 0.05 in the correlation of the GEBV of young bulls with their results after progeny testing. Only small differences in correlations were found in dependency on the methods used for the determination of G and in dependency on the weight used in blending G with A. Both EBV and GEBV in the older set showed higher correlations with the GEBV of the newer set than the EBV of the newer set.

Keywords: genomic breeding value; single-step prediction; first lactation; genomic relationship; genetic trend

Published: April 30, 2012  Show citation

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Přibyl J, Haman J, Kott T, Přibylová J, Šimečková M, Vostrý L, et al.. Single-step prediction of genomic breeding value in a small dairy cattle population with strong import of foreign genes. Czech J. Anim. Sci. 2012;57(4):151-159. doi: 10.17221/5890-CJAS.
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References

  1. Aguilar I., Misztal I., Johnson D.L., Legarra A., Tsuruta S., Lawlor T.J. (2010): Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 93, 743-752. Go to original source... Go to PubMed...
  2. Aguilar I., Misztal I., Tsuruta S., Wiggans G.R., Lawlor T.J. (2011): Multiple trait genomic evaluation of conception rate in Holsteins. Journal of Dairy Science, 94, 2621-2624. Go to original source... Go to PubMed...
  3. Bömcke E., Soyeurt H., Szydlowski M., Gengler N. (2009): How to combine pedigree and marker information into a single estimator for the calculation of relationships? In: Proc. 60 th Annu. Mtg. European Association for Animal Production (EAAP). Barcelona, Spain.
  4. Chen C.Y, Misztal I., Aguilar I., Tsuruta S., Meuwissen T.H.E., Aggrey S.E., Wing T., Muir W.M. (2011): Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens. Journal of Animal Science, 89, 23-28. Go to original source... Go to PubMed...
  5. Christensen O.F., Lund M.S. (2010): Genomic prediction when some animals are not genotyped. Genetics Selection Evolution, 42, 2. Go to original source... Go to PubMed...
  6. Ducrocq, V. (2011): Where are we heading to with genomics in dairy cattle evaluations? Interbull Technical Workshop: Establishing the framework for international genomic evaluations. 27th-28th Feb. 2011, Guelph, Canada.
  7. Forni S., Aguilar I., Misztal I. (2011): Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. Genetics Selection Evolution, 43, 1. Go to original source... Go to PubMed...
  8. Guo S.W. (1996): Variation in genetic identity among relatives. Human Heredity, 46, 61-70. Go to original source... Go to PubMed...
  9. Hayes B.J., Bowman P.J., Chamberlain A.J., Goddard M.E. (2009): Invited review: Genomic selection in dairy cattle: progress and challenges. Journal of Dairy Science, 92, 433-443. Go to original source... Go to PubMed...
  10. Komprej A., Gorjanc G., Kompan D., Kovač M. (2009): Covariance components by a repeatability model in Slovenian dairy sheep using test-day records. Czech Journal of Animal Science, 54, 426-434. Go to original source...
  11. Krejčová H., Přibyl J., Přibylová J., Štípková M., Mielenz N. (2008): Genetic evaluation of daily gains of dualpurpose bulls using a random regression model. Czech Journal of Animal Science, 53, 227-237. Go to original source...
  12. Legarra A., Aguilar I., Misztal I. (2009): A relationship matrix including full pedigree and genomic information. Journal of Dairy Science, 92, 4656-4663. Go to original source... Go to PubMed...
  13. Madsen P., Jensen J. (2008): DMU - a package for analysing multivariate mixed models. Version 6, release 4.7. 33 pp. Available from http://dmu.agrsci.dk
  14. Meuwissen T.H.E., Hayes B.J., Goddard M.E. (2001): Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, 1819-1829. Go to original source... Go to PubMed...
  15. Misztal I., Tsuruta S., Strabel T., Auvray B., Druet T., Lee D.H. (2002): BLUPF90 and related programs (BGF90). 7th WCGALP, 19th-23rd Aug. 2002, Montpellier, France.
  16. Misztal I., Legarra A., Aguilar I. (2009): Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. Journal of Dairy Science, 92, 4648-4655. Go to original source... Go to PubMed...
  17. Misztal I., Aguilar I., Legarra A., Tsuruta S., Johnson D.L., Lawlor T.J. (2010): A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation. 9th WCGALP, 1st-6th Aug. 2010, Leipzig, Germany.
  18. Plemdat (2011): Available from www.plemdat.cz.
  19. Poschadel N., Mayer M. (2011): Realisirte Verwandtschaftsmatrizen und Zuchtwerschätzung für die genomische Selektion - eine Übersicht. Züchtungskunde, 83, 167-181.
  20. Přibyl J. (1995): A way of using markers for farm animals selection. Živočišná výroba, 40, 375-382. (in Czech)
  21. Přibyl J., Řehout V., Čítek J., Přibylová J. (2010): Genetic evaluation of dairy cattle using a simple heritable genetic ground. Journal of the Science of Food and Agriculture, 90, 1765-1773. Go to original source... Go to PubMed...
  22. Schaeffer L.R. (2006): Strategy for applying genome-wide selection in dairy cattle. Journal of Animal Breeding and Genetics, 123, 218-223. Go to original source... Go to PubMed...
  23. Tsuruta S., Misztal I., Aguilar I., Lawlor T.J. (2011): Multiple-trait genetic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Journal of Dairy Science, 94, 4198-4204. Go to original source... Go to PubMed...
  24. VanRaden P.M. (2008): Efficient methods to compute genomic predictions. Journal of Dairy Science, 91, 4414-4423. Go to original source... Go to PubMed...
  25. VanRaden P.M., Van Tassell C.P., Wiggans G.R., Sonstegard T.S., Schnabel R.D., Taylor J.F., Schenkel F.S. (2009): Invited review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science, 92, 16-24. Go to original source... Go to PubMed...
  26. Verbyla K.L., Calus M.P., Mulder H.A., de Haas Y., Veerkamp R.F. (2010): Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information. Journal of Dairy Science, 3, 2757-2764. Go to original source... Go to PubMed...
  27. Vostrý L., Přibyl J., Jakubec V., Veselá Z., Majzlík I. (2008): Selection of a suitable definition of environment for the estimation of genotype × environment interaction in the weaning weight of beef cattle. Czech Journal of Animal Science, 53, 407-417. Go to original source...
  28. Wiggans G.R., Sonstegard T.S., VanRaden P.M., Matukumalli L.K., Schnabel R.D., Taylor J.F., Schenkel F.S., Van Tassell C.P. (2009): Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada. Journal of Dairy Science, 2, 3431-3436. Go to original source... Go to PubMed...
  29. Zavadilová L., Němcová E., Štípková M., Bouška J. (2009): Relationships between longevity and conformation traits in Czech Fleckvieh cows. Czech Journal of Animal Science, 54, 385-394. Go to original source...
  30. Zavadilová L., Jamrozik J., Schaeffer L.R. (2005): Genetic parameters for test day model with random regressions for production traits of Czech Holstein cattle. Czech Journal of Animal Science, 50, 142-154. Go to original source...

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