A comparison of dairy cattle breeding designs that use genomic selection

Different dairy cattle breeding schemes were compared using stochastic simulations, in which the accuracy of the genomic breeding values was dependent on the structure of the breeding scheme, through the availability of new genotyped animals with phenotypic information. Most studies that predict the gain by implementing genomic selection apply a deterministic approach that requires assumptions about the accuracy of the genomic breeding values. The achieved genetic gain, when genomic selection was the only selection method to directly identify elite sires for widespread use and progeny testing was omitted, was compared with using genomic selection for preselection of young bulls for progeny testing and to a conventional progeny test scheme. The rate of inbreeding could be reduced by selecting more sires every year. Selecting 20 sires directly on their genomic breeding values gave a higher genetic gain than any progeny testing scheme, with the same rate of inbreeding as the schemes that used genornic selection for preselection of bulls before progeny testing. The genomic selection breeding schemes could reduce the rate of inbreeding and still increase genetic gain, compared with the conventional breeding scheme. Because progeny testing is expensive, the breeding scheme omitting the progeny test will he the cheapest one. Keeping the progeny test and use of genomic selection for preselection still has some advantages. It gives higher accuracy of breeding values and does not require a. complete restructuring of the breeding program. Comparing at the same rate of inbreeding, using genomic selection for elite sire selection only gives a 13% increase in genetic gain; compared with using genomic selection for preselection. One way to reduce the costs of the scheme where genomic selection was used. for preselection is to reduce the number of progeny tested bulls. This was here achieved without getting lower genetic gain or a higher rate of inbreeding.