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Genomic Prediction for Abortion in Lactating Holstein Dairy Cows.
Robert Wijma1, Daniel J Weigel1, Natascha Vukasinovic1
1Zoetis Inc., 333 Portage Street, Kalamazoo, MI 49007, USA.
Animals : an Open Access Journal From MDPI
|August 26, 2022
Summary
Genomic predictions for dairy cow abortions were developed using producer data. Cows with higher genomic predictions showed a lower abortion rate, aiding in selecting healthier, more profitable animals.
Area of Science:
- Animal Genetics
- Dairy Science
- Reproductive Biology
Background:
- Abortion in dairy cattle leads to significant economic losses.
- Genetic factors contribute to the etiology of bovine abortions.
- Developing accurate genomic predictions is crucial for dairy herd management.
Purpose of the Study:
- To develop genomic predictions for cow abortions in Holstein dairy cattle.
- To evaluate the efficacy of these genomic predictions in commercial herds.
- To identify genetic markers associated with abortion risk.
Main Methods:
- Utilized producer-recorded phenotypic data, pedigree, and genotypes.
- Applied single-step genomic best linear unbiased prediction (ssGBLUP) methodology.
- Analyzed abortion as a binary outcome using a threshold model.
Main Results:
- Additive genetic variance for abortion was 0.1235, with a heritability of 0.0773.
- Mean reliability of genomic predictions was 42% across 1,662,251 animals.
- Genomic predictions effectively differentiated abortion risk (16.6% vs. 11.0% in extreme groups).
Conclusions:
- Genomic predictions for cow abortion (Z_Abort) can be accurately developed.
- Selection based on Z_Abort can reduce abortion incidence in dairy herds.
- Integrating Z_Abort into selection indices enhances profitability and animal health.
