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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #332113

Research Project: Improving Genetic Predictions in Dairy Animals Using Phenotypic and Genomic Information

Location: Animal Genomics and Improvement Laboratory

Title: Evaluation of genetic components in traits related to superovulation, in vitro fertilization, and embryo transfer in Holstein cattle

Author
item Parker Gaddis, Kristen - University Of Florida
item Dikmen, Serdal - Uludag University
item Null, Daniel
item Cole, John
item Hansen, Peter - University Of Florida

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/21/2016
Publication Date: 4/1/2017
Citation: Parker Gaddis, K.L., Dikmen, S., Null, D.J., Cole, J.B., Hansen, P.J. 2017. Evaluation of genetic components in traits related to superovulation, in vitro fertilization, and embryo transfer in Holstein cattle. Journal of Dairy Science. 100(4):2877-2891.

Interpretive Summary: Reproductive technologies such as superovulation and embryo transfer allow superior females to produce many more offspring than in traditional breeding programs. In addition to high cost, these technologies are also associated with variable animal response. Heritability was estimated for traits related to superovulation, in vitro fertilization, and embryo transfer in Holsteins. Traits were lowly to moderately heritable, indicating that selection would be possible in many cases. Associated regions of the genome were also investigated, with several being similar to regions previously associated with other fertility traits.

Technical Abstract: The objectives of this study were to estimate variance components and identify regions of the genome associated with traits related to embryo transfer in Holsteins. Reproductive technologies are used in the dairy industry to increase the reproductive rate of superior females. A drawback of these methods remains the variability of animal responses to the procedures. If some variability can be explained genetically, selection can be used to improve animal response. Data collected from a Holstein dairy farm in Florida from 2008 to 2015 included 926 superovulation records (number of structures recovered and number of good embryos), 628 in vitro fertilization records (number of oocytes collected, number of cleaved embryos, number of high- and low-quality embryos, and number of transferrable embryos), and 12,089 embryo transfer records (pregnancy success). Two methods of transformation (logarithmic and Anscombe) were applied to count variables and results were compared. Univariate animal models were fitted for each trait with the exception of pregnancy success after embryo transfer. Due to the binary nature of the latter trait, a threshold liability model was fitted that accounted for the genetic effect of both the recipient and the embryo. Both transformation methods produced similar results. Single-step genomic BLUP analyses were performed and SNP effects estimated for traits with a significant genetic component. Heritability of number of structures recovered and number of good embryos when log-transformed were 0.27 ± 0.08 and 0.15 ± 0.07, respectively. Heritability estimates from the in vitro fertilization data ranged from 0.01 ± 0.08 to 0.21 ± 0.15, but were not significantly (P < 0.05) different from zero. Recipient and embryo heritability (SD) of pregnancy success after embryo transfer was 0.03 (0.01) and 0.02 (0.01), respectively. The 10-SNP window explaining the largest proportion of variance (0.37%) for total structures collected was located on chromosome 8 beginning at 55,663,248 bp. Similar regions were identified for number of good embryos, with the largest proportion of variance (0.43 %) explained by a 10-SNP window on chromosome 14 beginning at 26,713,734 bp. Results indicate that there is a genetic component for some traits related to superovulation and that selection should be possible. Moreover, the genetic component for superovulation traits involves some genomic regions that are similar to those for other fertility traits currently evaluated.