Effect of Genetic and Environmental Factors on Twin Pregnancy in Primiparous Dairy Cows

SIMPLE SUMMARY: The biological and economic impacts of pregnancy loss in dairy herds are well recognized. Twin pregnancies compromise the health and wellbeing of cattle. The use of genomic testing for production traits and fitness traits to select replacement heifers is increasing in commercial dairy farms. Recently, a genomic prediction for twin pregnancies has been developed. The abortion of twin calves or parturition in the delivery of twins have been associated with the twin pregnancy trait (TWIN). However, the incidence of twins at abortion or at parturition are not a true reflection of twin pregnancy. A large number of pregnancy losses and twin reduction during the early fetal period are beyond clinical control. The rate of twin reduction is much higher than the rates of abortion and twin deliveries. The aim of this study was to evaluate factors affecting the incidence of twin pregnancies in high-producing primiparous dairy cows, with special emphasis placed on the genomic prediction values for twin pregnancy. Our study population of primiparous cows proved valuable in identifying factors other than genomic predictive values influencing the twin pregnancy rate. The photoperiod, milk production, and estrus synchronization protocol for fixed-time artificial insemination were found to significantly influence the rates of twin pregnancy. ABSTRACT: Twin pregnancies are highly undesirable in dairy cattle; they compromise the health and wellbeing of a cow and dramatically impair the farm economy. Recently, a genomic prediction for twin pregnancies has been developed. The objective of this study was to assess environmental and management risk factors affecting the incidence of twin pregnancies in high-producing dairy cows in their first lactation, with a special emphasis placed on the genomic prediction values of twin pregnancy. Our study population of primiparous cows proved valuable in identifying factors other than genomic predictive values that influence twin pregnancy rates. The odds ratio for twin pregnancies was 0.85 (p < 0.0001) for each unit of a prediction value increase, 3.5 (p = 0.023) for cows becoming pregnant during the negative photoperiod, and 0.33 (p = 0.016) for cows producing ≥42 kg of milk at AI, compared with the remaining cows who produced <42 kg of milk. As a general conclusion, the practical implication of our findings is that genomic prediction values can identify the risk of twin pregnancy at a herd level. Given the cumulative effect of genomic selection, selecting animals with a reduced genetic risk of twin pregnancies can contribute to reducing the incidence of twin pregnancies in dairy herds.