|GUINAN, FIONA - University Of Georgia|
|WIGGANS, GEORGE - Council On Dairy Cattle Breeding|
|NORMAN, HOWARD - Council On Dairy Cattle Breeding|
|DURR, JOAO - Council On Dairy Cattle Breeding|
|COLE, JOHN - Former ARS Employee|
|Van Tassell, Curtis - Curt|
|MISZTAL, IGNACY - University Of Georgia|
|LOURENCO, DANIELA - University Of Georgia|
Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/6/2022
Publication Date: 2/1/2023
Citation: Guinan, F.L., Wiggans, G.R., Norman, H.D., Durr, J.W., Cole, J.B., Van Tassell, C.P., Misztal, I., Lourenco, D. 2023. Changes in genetic trends in US dairy cattle since the implementation of genomic evaluations. Journal of Dairy Science. 106(2):1110–1129. https://doi.org/10.3168/jds.2022-22205.
Interpretive Summary: Multistep genomic evaluations for US dairy cattle were first implemented in 2009 for Holstein, Jersey and Brown Swiss dairy cattle breeds. In contrast, the adoption of genomics for Ayrshire and Guernsey is more recent. We investigated the genetic trends, inbreeding levels, and generation intervals since 1975 for the five dairy cattle breeds receiving genomic evaluations. Holstein and Jersey have benefited most from genomics, with up to an almost 6-fold increase in genetic gain in fat yield for Holstein bulls, nonetheless, with a rise in inbreeding levels. The progress made by breeds other than Holstein and Jersey is still small because of the lower usage of bulls and fewer genotypes and phenotypes available. Expanding the benefits of genomics for those breeds would require more comprehensive adoption of this technology and market incentives.
Technical Abstract: Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Assumptions of genetic improvement must be addressed to quantify the magnitude and direction of change. Genetic trends of US dairy cattle breeds were examined to determine the genetic gain since the implementation of genomic evaluations in 2009. Breeds included Ayrshire (AY), Brown Swiss (BS), Guernsey (GU), Holstein (HO), and Jersey (JE), which were characterized by the evaluation breed the animal received. Mean Predicted Breeding Values (PBV) were analyzed per year to calculate genetic trends for bulls and cows. The data set contained 154,602 bulls and 27,802,645 cows born since 1975. Breakpoints were estimated using linear regression, and nonlinear regression was used to fit the piecewise model for the small sample number in some years. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat and protein yields, Somatic Cell Score (SCS), Productive Life (PL), Daughter Pregnancy Rate (DPR), and Livability (LIV) PBV were documented. The number of bulls obtaining genomic evaluations has increased 75% since 2010, and in 2017, 100% of bulls in this dataset were genotyped. Genotyped cows have increased 20% in the same period. Overall, production traits have increased steadily over time as expected. Holstein and Jersey have benefited most from genomics, with up to almost a 6-fold increase in genetic gain since 2009. Due to the low number of observations, trends for AY, BS, and GU are difficult to infer from. Trends in fertility are most substantial – most breeds are trending downwards, DPR for JE has been decreasing steadily since 1975 for bulls and cows. Levels of genomic inbreeding coefficients are increasing at an alarming rate in HO bulls and cows. In 2017, genomic inbreeding levels were at 12.64% for bulls and 8.82% for cows. A suggestion to control this is to apply a negative weight (genomic inbreeding coefficient) to the selection index of bulls with high genomic inbreeding levels. The number of colored breed bulls in the U.S. is currently at a very low level, and this number will only increase with a market incentive or with additional breed association involvement. Increased education and extension could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and diversity in the genomic selection era.