Including overseas performance information in genomic evaluations of Australian dairy cattle

Journal of Dairy Science

Volumn 98, Issue 5, 2015, Pages 3443-3459

  Haile Mariam, M ^a,b   Pryce, J E ^a,b   Schrooten, C ^c   Hayes, B J ^a,b  

^a LA TROBE UNIVERSITY   (Australia)

^b LA TROBE UNIVERSITY   (Australia)

^c CRV   (Netherlands)

Author keywords

Daughter trait deviation; Deregressed proof; Genomic prediction; Reliability

Indexed keywords

BOS;

ANIMAL; AUSTRALIA; BIOLOGICAL MODEL; BOVINE; BREEDING; CELL COUNT; CLASSIFICATION; EUROPE; FEMALE; FERTILITY; GENETIC DATABASE; GENETIC SELECTION; GENETICS; GENOMICS; GENOTYPE; GENOTYPE ENVIRONMENT INTERACTION; MILK; NORTH AMERICA; PHENOTYPE; PROCEDURES; REPRODUCIBILITY; SECRETION (PROCESS); SINGLE NUCLEOTIDE POLYMORPHISM;

ANIMALS; AUSTRALIA; BREEDING; CATTLE; CELL COUNT; DATABASES, GENETIC; EUROPE; FEMALE; FERTILITY; GENE-ENVIRONMENT INTERACTION; GENOMICS; GENOTYPE; MILK; MODELS, GENETIC; NORTH AMERICA; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; REPRODUCIBILITY OF RESULTS; SELECTION, GENETIC;

EID: 84928059262     PISSN: 00220302     EISSN: 15253198     Source Type: Journal    
DOI: 10.3168/jds.2014-8785     Document Type: Article

References (34)

1. Amer P.R., Banos G. Implications of avoiding overlap between training and testing data sets when evaluating genomic predictions of genetic merit. J. Dairy Sci. 2010, 93:3320-3330.
2. Battagin M., Forabosco F., Jakobsen J.H., Penasa M., Lawlor T.J., Cassandro M. International genetic evaluation of Holstein bulls for overall type traits and body condition score. J. Dairy Sci. 2012, 95:4721-4731.
3. Battagin M., Forabosco F., Penasa M., Cassandro M. Cluster analysis on across-country genetic correlations for overall type traits and body condition score of Holstein bulls. Livest. Sci. 2013, 151:108-114.
4. Bijma P. Accuracies of estimated breeding values from ordinary genetic evaluations do not reflect the correlation between true and estimated breeding values in selected populations. J. Anim. Breed. Genet. 2012, 129:345-358.
5. Brøndum R.F., Rius-Vilarrasa E., Strandén I., Su G., Guldbrandtsen B., Fikse W.F., Lund M.S. Reliabilities of genomic prediction using combined reference data of the Nordic Red dairy cattle populations. J. Dairy Sci. 2011, 94:4700-4707.
6. Browning B.L., Browning S.R. A unified approach to genotype imputation and haplotype phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 2009, 84:210-223.
7. Clark S.A., Hickey J.M., Daetwyler H.D., van der Werf J.H.J. The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes. Genet. Sel. Evol. 2012, 44:4.
8. Daetwyler H.D., Calus M.P.L., Pong-Wong R., de los Campos G., Hickey J.M. Genomic prediction in animals and plants: Simulation of data, validation, reporting, and benchmarking. Genetics 2013, 193:347-365.
9. Daetwyler H.D., Swan A.A., van der Werf J.H.J., Hayes B.J. Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation. Genet. Sel. Evol. 2012, 44:33.
10. Daetwyler H.D., Villanueva B., Woolliams J.A. Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS ONE 2008, 3:e3395.
11. de Roos A.P.W., Hayes B.J., Spelman R.J., Goddard M.E. Linkage disequilibrium and persistence of phase on Holstein-Friesian, Jersey, and Angus cattle. Genetics 2008, 179:1503-1512.
12. Erbe M., Hayes B.J., Matukumalli L.K., Goswami S., Bowman P.J., Reich C.M., Mason B.A., Goddard M.E. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. J. Dairy Sci. 2012, 95:4114-4129.
13. Garrick D.J., Taylor J.F., Fernando R.L. Deregressing estimated breeding values and weighting information for genomic regression analyses. Genet. Sel. Evol. 2009, 41:55.
14. Gilmour, A. R., B. J. Gogel, B. R. Cullis, and R. Thompson. 2009. ASReml User Guide Release 3.0 VSN International Ltd., Hemel Hempstead, UK.
15. Goddard M. Genomic selection: Prediction of accuracy and maximization of long term response. Genetica 2009, 136:245-257.
16. Grisart B., Farnir F., Karim L., Cambisano N., Kim J.J., Kvasz A., Mni M., Simon P., Frere J.M., Coppieters W., Georges M. Genetic and functional confirmation of the causality of the DGAT1 K232A quantitative trait nucleotide in affecting milk yield and composition. Proc. Natl. Acad. Sci. USA 2004, 101:2398-2403.
17. Habier D., Tetens J., Seefried F.R., Lichtner P., Thaller G. The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genet. Sel. Evol. 2010, 42:5.
18. Habier D., Fernando R.L., Kizilkaya K., Garrick D.J. Extension of the Bayesian alphabet for genomic selection. BMC Bioinformatics 2011, 12:186.
19. Haile-Mariam, J., E. Pryce, and B. Hayes. 2014. Analyses of functional traits with indicator traits to improve genomic reliability in Australian Holstein cattle using domestic daughter trait deviation or de-regressed proofs as response variable. Accessed Nov. 2014. http://https://asas.org/docs/default-source/wcgalp-proceedings-oral/298_paper_10023_manuscript_1727_0.pdf.
20. Haile-Mariam M., Bowman P.J., Pryce J.E. Genetic analyses of fertility in Holstein herds with low and high mean calving intervals and in Jersey herds. J. Dairy Sci. 2013, 96:655-667. a.
21. Haile-Mariam M., Nieuwhof G.J., Beard K.T., Konstantinov K.V., Hayes B.J. Comparison of heritabilities of dairy traits in Australian Holstein-Friesian cattle from genomic and pedigree data and implications for genomic evaluations. J. Anim. Breed. Genet. 2013, 130:20-31. b.
22. Hayes B.J., Bowman P.J., Chamberlain A.C., Verbyla K., Goddard M.E. Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genet. Sel. Evol. 2009, 41:51.
23. Interbull. 2013. Appendix I. Sire standard deviations in diagonal and genetic correlations below diagonal. Accessed Oct. 2013. http://http://www.interbull.org/static/mace:evaluations_archive/eval/prod-appen1-141.pdf.
24. Jensen J., Su G., Madsen P. Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle. BMC Genet. 2012, 13:44.
25. Liu Z. Deregressing MACE proofs for genomic evaluations 2009, Proteje Meeting, Brussels, Belgium.
26. Lund M.S., de Roos A.P., Vries A.G., Druet T., Ducrocq V., Fritz S., Guillaume F., Guldbrandtsen B., Liu Z., Reents R., Schrooten C., Seefried F., Su G. A common reference population from four European Holstein populations increases reliability of genomic predictions. Genet. Sel. Evol. 2011, 43:43.
27. Matukumalli L.K., Lawley C.T., Schnabel R.D., Taylor J.F., Allan M.F., Heaton M.P., O'Connell J., Moore S.S., Smith T.P.L., Sonstegard T.S., Van Tassell C.P. Development and characterization of a high density SNP genotyping assay for cattle. PLoS ONE 2009, 4:e5350.
28. Nieuwhof G.J., Beard K.T., Konstantinov K.V., Bowman P.J., Hayes B.J. Implementation of Genomics in Australia. Interbull Bull. 2010, 42:35-39.
29. Pszczola M., Strabel T., Mulder H.A., Calus M.P.L. Reliability of genomic selection for animals with different relationships within and to the reference population. J. Dairy Sci. 2012, 95:389-400.
30. Thomsen H., Reinsch N., Xu N., Looft C., Grupe S., Kühn C., Brockmann G.A., Schwerin M., Leyhe-Horn B., Hiendleder S., Erhardt G., Medjugorac I., Russ I., Förster M., Brenig B., Reinhardt F., Reents R., Blümel J., Averdunk G., Kalm E. Comparison of estimated breeding values, daughter yield deviations and de-regressed proofs within a whole genome scan for QTL. J. Anim. Breed. Genet. 2001, 118:357-370.
31. VanRaden P.M., Olson K.M., Null D.J., Sargolzaei M., Winters M., van Kaam J.B.C.H.M. Reliability increases from combining 50,000- and 777,000-marker genotypes from four countries. Interbull Bull. 2012, 46:75-79.
32. VanRaden P.M., Wiggans G.R. Derivation, calculation, and use of national animal model information. J. Dairy Sci. 1991, 74:2737-2746.
33. Vollema A.R., Groen A.B.F. A comparison of breeding value predictors for longevity using a linear model and survival analysis. J. Dairy Sci. 1998, 81:3315-3320.
34. Yang J., Benyamin B., McEvoy B., Gordon S., Henders A., Nyholt D., Madden P., Heath A., Martin N., Montgomery G., Goddard M.E., Visscher P.M. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 2010, 42:565-569.