Sustainable dairy cattle selection in the genomic era
Didier Boichard, Vincent Ducrocq, Sébastien Fritz
Abstract
Didier Boichard, Vincent Ducrocq, Sébastien Fritz
Abstract
Genomic selection offers considerable flexibility to increase genetic trends in dairy cattle breeding. It is also an opportunity for more sustainable breeding, in terms of breeding goal and genetic variability. With a shorter generation interval, there is a big risk of increasing inbreeding if semen dissemination policy of elite bulls is not changed. However, using a large number of young bulls as service bulls and bull sires is a solution for both maximizing genetic trend while reducing inbreeding trend. Female genotyping is a key challenge for within-herd selection but, more importantly, for selection of new traits and for replacement of current reference populations based upon progeny-tested bulls. Genomic selection also opens new avenues for more customized breeding across herds or production systems. A big challenge is to reduce the dependency of genomic predictions on relationship between candidates and the reference population. A strong effort is presently dedicated to integrating genome sequence information into predictions, to improve their accuracy and persistency. In the longer term, further customization of selection will be possible by accounting for G × E interactions. Important developments are also necessary to decrease loss of favourable alleles through genetic drift.
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Genomic selection offers considerable flexibility to increase genetic trends in dairy cattle breeding. It is also an opportunity for more sustainable breeding, in terms of breeding goal and genetic variability. With a shorter generation interval, there is a big risk of increasing inbreeding if semen dissemination policy of elite bulls is not changed. However, using a large number of young bulls as service bulls and bull sires is a solution for both maximizing genetic trend while reducing inbreeding trend. Female genotyping is a key challenge for within-herd selection but, more importantly, for selection of new traits and for replacement of current reference populations based upon progeny-tested bulls. Genomic selection also opens new avenues for more customized breeding across herds or production systems. A big challenge is to reduce the dependency of genomic predictions on relationship between candidates and the reference population. A strong effort is presently dedicated to integrating genome sequence information into predictions, to improve their accuracy and persistency. In the longer term, further customization of selection will be possible by accounting for G × E interactions. Important developments are also necessary to decrease loss of favourable alleles through genetic drift.
Key concepts: Biology, Inbreeding, Selection (genetic algorithm), Genomic selection, Genetic gain, Biotechnology, Herd, Population