Genomic selection in dairy cattle: Integration of DNA testing into breeding programs

By J. Schefers, Kent A. Weigel. 2012

143 citations recorded by the source corpus.

Genomic selection offers many advantages with regard to improving the rate of genetic gain in dairy cattle breeding programs. The most important factors that contribute to faster genetic gain include • A greater accuracy of predicted genetic merit for young animals. • A shorter generation interval because of heavier use of young, genetically superior males and females. • An increased intensity of selection because breeders can use genomic testing to screen a larger group of potentially elite animals. By increasing the accuracy and intensity of selection and shortening the generation interval, the rate of genetic progress for economically important dairy traits can be approximately doubled. bulls with high genetic merit. Before progeny testing a young bull, the average estimated breeding value (EBV) of his sire and dam, which is commonly referred to as parent average, was used to select young bulls with the highest genetic merit and had an accuracy (reliability) of only 30 to 40%. In a progeny-testing scheme, a group of elite cows was identifi ed as potential dams of young bulls (i.e., bull mothers). Progeny testing was necessary because most traits of economic importance in dairy cattle (e.g., milk production) are sex-limited and can be measured only in females. These bull mothers were mated to elite progeny-tested sires from the previous generation for the specifi c purpose of producing bull calves. Once these young bulls reached sexual maturity, which typically occurred at about 12 months of age, they were mated to a large number of cows on commercial farms, with the goal of producing approximately 100 daughters. Approximately 3 years later, the daughters of these young bulls would begin lactating, and this information was used to calculate the EBV of their sires for milk production and other key traits, which typically had reliabilities of 75 to 85%. At this point, these bulls were approximately 4.5 years of age, and the AI companies would decide which bulls should be culled and which bulls should be marketed to dairy farmers for the purpose of siring the next generation of replacement heifers. Overall, progeny-testing schemes are time consuming and costly because the AI companies have to wait many years to obtain genetic predictions with suffi cient accuracy for making selection decisions, and in the meantime, hundreds of bulls are housed “in waiting” while phenotypes are measured on tens of thousands of their daughters. The objective of this review is to describe how genomics will affect genetic progress and breeding programs in the future.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/45ec648551ea55ce9c21cb3c725eaa69c3ae0f23

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Citations in the corpus

Genomic selection in forest tree breeding: the concept and an outlook to the future (2014, methodology): “For example, in dairy cattle, with GS, genomic bulls are selected at 21 months instead of 54 months using traditional progeny testing (Schefers and Weigel 2012).”
Implementation of genomic selection in the poultry industry (2016, methodology): “In a single step setting, multiline data can also be utilized provided the genomic relationship matrix is scaled correctly (Simeone et al., 2012).”