Effects of preselection of genotyped animals on reliability and bias of genomic prediction in dairy cattle
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Objective: Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. Methods: We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. Results: The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. Conclusion: Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.
Abstract
Objective: Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. Methods: We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. Results: The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. Conclusion: Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.
참고문헌 (30)
- Meuwissen THE, "Prediction of total genetic value using genome-wide dense marker maps", Genetics, 157, pp.1819~1829 (2001)
- Mäntysaari E, "Interbull validation test for genomic evaluations", Interbull bulletin, 41, pp.4~5 (2010)
- Falconer DS, "Introduction to quantitative genetics" (1996), Longman
- Schaeffer LR, "Strategy for applying genome-wide selection in dairy cattle", J Anim Breed Genet, 123, pp.218~223 (2006)
- Van Grevenhof EM, "Response to genomic selection : The bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting", Genet Sel Evol, 44, pp.26~ (2012)
- Daetwyler HD, "Inbreeding in genome-wide selection", J Anim Breed Genet, 124, pp.369~376 (2007)
- Jenko J, "Cow genotyping strategies for genomic selection in a small dairy cattle population", J Dairy Sci, 100, pp.439~452 (2017)
- Buch LH, "The value of cows in reference populations for genomic selection of new functional traits", Animal, 6, pp.880~886 (2012)
- Ding X, "Accuracy of genomic prediction for milk production traits in the Chinese Holstein population using a reference population consisting of cows", J Dairy Sci, 96, pp.5315~5323 (2013)
- Uemoto Y, "Effect of genotyped cows in the reference population on the genomic evaluation of Holstein cattle", Animal, 11, pp.382~393 (2017)
- Calus MPL, "Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies", J Dairy Sci, 96, pp.6703~6715 (2013)
- Pryce JE, "Symposium review: Building a better cow—the Australian experience and future perspectives", J Dairy Sci, 101, pp.3702~3713 (2018)
- Cunningham EP, "Multi-stage index selection", Theor Appl Genet, 46, pp.55~61 (1975)
- Van Raden PM, "Invited review : Reliability of genomic predictions for North American Holstein bulls", J Dairy Sci, 92, pp.16~24 (2009)
- Olson KM, "Differences among methods to validate genomic evaluations for dairy cattle", J Dairy Sci, 94, pp.2613~2620 (2011)
- Daetwyler HD, "Accuracy of predicting the genetic risk of disease using a genome-wide approach", PLoS One, 3, pp.e3395~ (2008)
- Hayes BJ, "Accuracy of genomic selection : comparing theory and results", Proc Assoc Advmt Anim Breed Genet, 18, pp.34~37 (2009)
- Garrick DJ, "Deregressing estimated breeding values and weighting information for genomic regression analyses", Genet Sel Evol, 41, pp.55~ (2009)
- Liu Z, "Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction", Genet Sel Evol, 43, pp.19~ (2011)
- Gonzalez-Recio O, "Incorporating heifer feed efficiency in the Australian selection index using genomic selection", J Dairy Sci, 97, pp.3883~3893 (2014)
- Weigel KA, "Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves on commercial dairy farms", J Dairy Sci, 95, pp.2215~2225 (2012)
- Thomasen JR, "Adding cows to the reference population makes a small dairy population competitive", J Dairy Sci, 97, pp.5822~5832 (2014)
- Pryce JE, "Symposium review: Building a better cow—The Australian experience and future perspectives", J Dairy Sci, 101, pp.3702~3713 (2018)
- Habier D, "The impact of genetic relationship information on genome-assisted breeding values", Genetics, 177, pp.2389~2397 (2007)
- Habier D, "The impact of genetic relationship information on genomic breeding values in German Holstein cattle", Genet Sel Evol, 42, pp.5~ (2010)
- Su G, "Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey", Animal, 10, pp.1067~1075 (2016)
- Goddard ME, "Genomic selection : prediction of accuracy and maximisation of long term response", Genetica, 136, pp.245~257 (2009)
- Solberg TR, "Genomic selection using different marker types and densities", J Anim Sci, 86, pp.2447~2454 (2008)
- Muir, WM, "Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters", J Anim Breed Genet, 124, pp.342~355 (2007)
- Su G, "Genomic prediction for Nordic red cattle using one-step and selection index blending", J Dairy Sci, 95, pp.909~917 (2012)