Predicted accuracy of and response to genomic selection for new traits in dairy cattle

Animal

Volumn 7, Issue 2, 2013, Pages 183-191

  Calus, M P L ^a   De Haas, Y ^a   Pszczola, M ^a,b   Veerkamp, R F ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b POZNA UNIVERSITY OF LIFE SCIENCES   (Poland)

Author keywords

genomic selection; new traits; reference populations; selection response

Indexed keywords

ANIMAL; ARTICLE; BIOLOGICAL MODEL; BREEDING; CATTLE; CROSS BREEDING; FEMALE; GENETIC SELECTION; GENETICS; GENOME; GENOTYPE; MALE; PHENOTYPE; PHYSIOLOGY; QUANTITATIVE TRAIT; QUANTITATIVE TRAIT LOCUS; SINGLE NUCLEOTIDE POLYMORPHISM;

ANIMALS; BREEDING; CATTLE; CROSSES, GENETIC; FEMALE; GENOME; GENOTYPE; MALE; MODELS, GENETIC; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; QUANTITATIVE TRAIT, HERITABLE; SELECTION, GENETIC;

BOS;

EID: 84872077949     PISSN: 17517311     EISSN: 1751732X     Source Type: Journal    
DOI: 10.1017/S1751731112001450     Document Type: Article

References (34)

1. Berry DP, Bastiaansen JWM, Veerkamp RF, Wijga S, Wall E, Berglund B and Calus MPL 2012. Genome-wide associations for fertility traits in Holstein-Friesian dairy cows using data from experimental research herds in four European countries. Animal 6, 1206-1215
2. Bijma P. Accuracies of estimated breeding values fromordinary genetic evaluations do not reflect the correlation between true and estimated breeding values in selected populations. Journal of Animal Breeding and Genetics, doi:10.1111/ j.1439-0388.2012.00991.x, Published online by Blackwell Verlag GmbH 22 February 2012
3. Buch LH, Sørensen MK, Berg P, Pedersen LD and Sørensen AC 2012. Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain. Journal of Animal Breeding and Genetics 129, 138-151
4. Bulmer M 1971. The effect of selection on genetic variability. The American Naturalist 105, 201-211
5. Calus MPL 2010. Genomic breeding value prediction: Methods and procedures. Animal 4, 157-164
6. Calus MPL and Veerkamp RF 2011. Accuracy of multi-Trait genomic selection using different methods. Genetics Selection Evolution 43, 26
7. Daetwyler HD 2009. Genome-wide evaluation of populations. PhD thesis. Wageningen University
8. Daetwyler HD, Villanueva B and Woolliams JA 2008. Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS One 3, e3395
9. de Haas Y, Windig JJ, Calus MPL, Dijkstra J, de Haan M, Bannink A and Veerkamp RF 2011. Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. Journal of Dairy Science 94, 6122-6134
10. de Roos APW, Hayes BJ and Goddard ME 2009. Reliability of genomic predictions across multiple populations. Genetics 183, 1545-1553
11. de Roos APW, Schrooten C, Veerkamp RF and van Arendonk JAM 2011. Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls. Journal of Dairy Science 94, 1559-1567
12. Dekkers J 2007. Prediction of response to marker-Assisted and genomic selection using selection index theory. Journal of Animal Breeding and Genetics 124, 331-341 (Pubitemid 350231125)
13. Goddard M 2009. Genomic selection: Prediction of accuracy and maximisation of long term response. Genetica 136, 245-257
14. Habier D, Fernando R and Dekkers J 2007. The impact of genetic relationship information on genome-Assisted breeding values. Genetics 177, 2389-2397 (Pubitemid 350277013)
15. Habier D, Tetens J, Seefried FR, Lichtner P and Thaller G 2010. The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genetics Selection Evolution 42, 5
16. Hayes B, Bowman P, Chamberlain A and Goddard M 2009. Invited review: Genomic selection in dairy cattle: Progress and challenges. Journal of Dairy Science 92, 433-443
17. Kirkpatrick BW, Shi X, Shook GE and Collins MT 2011. Whole-genome association analysis of susceptibility to paratuberculosis in Holstein cattle. Animal Genetics 42, 149-160
18. Lillehammer M, Meuwissen THE and Sonesson AK 2011. A comparison of dairy cattle breeding designs that use genomic selection. Journal of Dairy Science 94, 493-500
19. Lund M, de Ross S, de Vries A, Druet T, Ducrocq V, Fritz S, Guillaume F, Guldbrandtsen B, Liu Z, Reents R, Schrooten C, Seefried F and Su G 2011 A common reference population from four European Holstein populations increases reliability of genomic predictions. Genetics Selection Evolution 43, 43
20. Meuwissen THE, Hayes BJ and Goddard ME 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819-1829 (Pubitemid 32298846)
21. Mrode R. 2005 Linear models for the prediction of animal breeding values CABI Publishing, Wallingford.
22. Mrode R 2005. Linear models for the prediction of animal breeding values. CABI Publishing, Wallingford. Pedersen LD, Kargo M, Berg P, Voergaard J, Buch LH and Sørensen AC 2012 Genomic selection strategies in dairy cattle breeding programmes: Sexed semen cannot replace multiple ovulation and embryo transfer as superior reproductive technology. Journal of Animal Breeding and Genetics 129, 152-163
23. Pérez-Cabal MA, Vazquez AI, Gianola D, Rosa GJM and Weigel KA 2012 Accuracy of genome enabled prediction in a dairy cattle population using different cross-validation layouts. Frontiers in Genetics 3, 27
24. Pryce JE, Goddard ME, Raadsma HW and Hayes BJ 2010. Deterministic models of breeding scheme designs that incorporate genomic selection. Journal of Dairy Science 93, 5455-5466
25. Pszczola M, Strabel T, Mulder HA and Calus MPL 2012. Reliability of direct genomic values for animals with different relationships within and to the reference population. Journal of Dairy Science 95, 389-400
26. Rutten MJM, Bijma P, Woolliams JA and van Arendonk JAM 2002. SelAction: Software to predict selection response and rate of inbreeding in livestock breeding programs. Journal of Heredity 93, 456-458 (Pubitemid 36268524)
27. Schrooten C, Bovenhuis H, van Arendonk JAM and Bijma P 2005. Genetic progress in multistage dairy cattle breeding schemes using genetic markers. Journal of Dairy Science 88, 1569-1581 (Pubitemid 41431277)
28. Sigurdsson A and Banos G 1995. Dependent-variables in international sire evaluations. Acta Agriculturae Scandinavica Section A - Animal Science 45, 209-217
29. Van Grevenhof EM 2011. Breeding against osteochondrosis. PhD thesis. Wageningen University
30. VanRaden PM and Wiggans GR 1991. Derivation, calculation, and use of national animal-model information. Journal of Dairy Science 74, 2737-2746
31. Veerkamp RF, Oldenbroek JK, Van Der Gaast HJ and Van Der Werf JHJ 2000 Genetic correlation between days until start of luteal activity and milk yield, energy balance, and live weights. Journal of Dairy Science 83, 577-583
32. Verbyla KL, Calus MPL, Mulder HA, de Haas Y and Veerkamp RF 2010 Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information. Journal of Dairy Science 93, 2757-2764
33. Wall E, Simm G and Moran D 2010. Developing breeding schemes to assist mitigation of greenhouse gas emissions. Animal 4, 366-376
34. Zhong S, Dekkers JCM, Fernando RL and Jannink J-L 2009. Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: A barley case study. Genetics 182, 355-364