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Article

Genomic Prediction for Twin Pregnancies

1
Zoetis Genetics, 333 Portage Street, Kalamazoo, MI 49007, USA
2
Zoetis Outcomes Research, 333 Portage Street, Kalamazoo, MI 49007, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Irina Garcia-Ispierto
Animals 2021, 11(3), 843; https://doi.org/10.3390/ani11030843
Received: 27 January 2021 / Revised: 25 February 2021 / Accepted: 1 March 2021 / Published: 16 March 2021
(This article belongs to the Special Issue Therapeutics of Twin Pregnancies in Dairy Cattle)
Twinning in dairy cattle is caused by many different factors, both genetic (i.e., inherited) and non-genetic (i.e., animal management). In dairy operations, twinning is an undesirable trait associated with other reproductive and metabolic diseases, higher operational costs, and higher rates of culling on farm. The animal welfare and economic impacts have resulted in the development of a genomic prediction for twinning (i.e., TWIN) by Zoetis such that producers can make informed breeding decisions for breeding Holstein females that are less likely to become pregnant with twins in a given lactation. This prediction is included in a holistic breeding tool (i.e., selection index) for producers so that they can improve multiple health, fertility, and production traits in parallel with reducing twinning when making breeding decisions for future generations. The objectives of the present study were (1) to describe how the twinning prediction was developed (and included in a selection index), (2) show that the prediction works effectively using real life farm data, and (3) propose how this genetic tool can be used in collaboration with management practices to proactively reduce twin pregnancies on farm. The results of this study provide evidence that twinning can be proactively managed on dairy farms using genetically powered tools.
Twinning is a multifactorial trait influenced by both genetic and environmental factors that can negatively impact animal welfare and economic sustainability on commercial dairy operations. To date, using genetic selection as a tool for reducing twinning rates on commercial dairies has been proposed, but not yet implemented. In response to this market need, Zoetis (Kalamazoo, MI, USA) has developed a genomic prediction for twin pregnancies, and included it in a comprehensive multitrait selection index. The objectives of this study were to (1) describe a genetic evaluation for twinning in Holstein cattle, (2) demonstrate the efficacy of the predictions, (3) propose strategies to reduce twin pregnancies using this information. Data were retrieved from commercial dairies and provided directly by producers upon obtaining their permission. The twin pregnancies trait (TWIN) was defined as a pregnancy resulting in birth or abortion of twin calves, classified as a binary (0,1) event, and analysed using a threshold animal model. Predictions for a subset of cows were compared to their on-farm twin records. The heritability for twin pregnancies was 0.088, and genomic predicted transmitting abilities ((g)PTAs) ranged from −7.45–20.79. Genetic correlations between TWIN and other traits were low, meaning that improvement for TWIN will not negatively impact improvement for other traits. TWIN was effectively demonstrated to identify cows most and least likely to experience a twin pregnancy in a given lactation, regardless of reproductive protocol used. Effective inclusion of the prediction in a multitrait selection index offers producers a comprehensive tool to inform selection and management decisions. When combined with sound management practices, this presents a compelling opportunity for dairy producers to proactively reduce the incidence of twin pregnancies on commercial dairy operations. View Full-Text
Keywords: genetics; genomics; twinning; Holstein; selection index; breeding strategy; prediction; STA genetics; genomics; twinning; Holstein; selection index; breeding strategy; prediction; STA
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MDPI and ACS Style

McGovern, S.P.; Weigel, D.J.; Fessenden, B.C.; Gonzalez-Peña, D.; Vukasinovic, N.; McNeel, A.K.; Di Croce, F.A. Genomic Prediction for Twin Pregnancies. Animals 2021, 11, 843. https://doi.org/10.3390/ani11030843

AMA Style

McGovern SP, Weigel DJ, Fessenden BC, Gonzalez-Peña D, Vukasinovic N, McNeel AK, Di Croce FA. Genomic Prediction for Twin Pregnancies. Animals. 2021; 11(3):843. https://doi.org/10.3390/ani11030843

Chicago/Turabian Style

McGovern, Shaileen P., Daniel J. Weigel, Brenda C. Fessenden, Dianelys Gonzalez-Peña, Natascha Vukasinovic, Anthony K. McNeel, and Fernando A. Di Croce. 2021. "Genomic Prediction for Twin Pregnancies" Animals 11, no. 3: 843. https://doi.org/10.3390/ani11030843

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