Effects of preselection of genotyped animals on reliability and bias of genomic prediction in dairy cattle

被引:2
|
作者
Togashi, Kenji [1 ]
Adachi, Kazunori [2 ]
Kurogi, Kazuhito [1 ]
Yasumori, Takanori [2 ]
Tokunaka, Kouichi [2 ]
Ogino, Atsushi [1 ]
Miyazaki, Yoshiyuki [1 ]
Watanabe, Toshio [1 ]
Takahashi, Tsutomu [2 ]
Moribe, Kimihiro [2 ]
机构
[1] Livestock Improvement Assoc Japan, Maebashi Inst Anim Sci, Maebashi, Gunma 3710121, Japan
[2] Livestock Improvement Assoc Japan, Koto Ku, Tokyo 1350041, Japan
来源
ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES | 2019年 / 32卷 / 02期
关键词
Reliability of Selection; Genomic Selection; Reference Population; Dairy Cattle; REFERENCE POPULATION; SELECTION; COWS; ACCURACY;
D O I
10.5713/ajas.18.0161
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
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.
引用
收藏
页码:159 / 169
页数:11
相关论文
共 50 条
  • [22] Genomic prediction of residual feed intake in US Holstein dairy cattle
    Li, B.
    VanRaden, P. M.
    Guduk, E.
    O'Connell, J. R.
    Null, D. J.
    Connor, E. E.
    VandeHaar, M. J.
    Tempelman, R. J.
    Weigel, K. A.
    Cole, J. B.
    JOURNAL OF DAIRY SCIENCE, 2020, 103 (03) : 2477 - 2486
  • [23] Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome
    Id-Lahoucine, Samir
    Casellas, Joaquim
    Miglior, Filippo
    Schenkel, Flavio S.
    Canovas, Angela
    FRONTIERS IN GENETICS, 2023, 14
  • [24] Improving the accuracy of genomic prediction in dairy cattle using the biologically annotated neural networks framework
    Wang, Xue
    Shi, Shaolei
    Khan, Md. Yousuf Ali
    Zhang, Zhe
    Zhang, Yi
    JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY, 2024, 15 (01)
  • [25] Reliabilities of genomic prediction using combined reference data of the Nordic Red dairy cattle populations
    Brondum, R. F.
    Rius-Vilarrasa, E.
    Stranden, I.
    Su, G.
    Guldbrandtsen, B.
    Fikse, W. F.
    Lund, M. S.
    JOURNAL OF DAIRY SCIENCE, 2011, 94 (09) : 4700 - 4707
  • [26] The feasibility of using low-density marker panels for genotype imputation and genomic prediction of crossbred dairy cattle of East Africa
    Aliloo, H.
    Mrode, R.
    Okeyo, A. M.
    Ni, G.
    Goddard, M. E.
    Gibson, J. P.
    JOURNAL OF DAIRY SCIENCE, 2018, 101 (10) : 9108 - 9127
  • [27] Inbreeding effects in dairy cattle populations - Part 2: Analyses using genomic data
    Wirth, Anna
    Dist, Ottmar
    ZUCHTUNGSKUNDE, 2024, 96 (04): : 276 - 296
  • [28] Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds
    Palombo, Valentino
    Pegolo, Sara
    Conte, Giuseppe
    Cesarani, Alberto
    Macciotta, Nicolo Pietro Paolo
    Stefanon, Bruno
    Ajmone Marsan, Paolo
    Mele, Marcello
    Cecchinato, Alessio
    D'Andrea, Mariasilvia
    JOURNAL OF ANIMAL BREEDING AND GENETICS, 2021, 138 (03) : 389 - 402
  • [29] Optimizing genomic prediction model given causal genes in a dairy cattle population
    Teng, Jinyan
    Huang, Shuwen
    Chen, Zitao
    Gao, Ning
    Ye, Shaopan
    Diao, Shuqi
    Ding, Xiangdong
    Yuan, Xiaolong
    Zhang, Hao
    Li, Jiaqi
    Zhang, Zhe
    JOURNAL OF DAIRY SCIENCE, 2020, 103 (11) : 10299 - 10310
  • [30] Genomic prediction in Nordic Red dairy cattle considering breed origin of alleles
    Guillenea, Ana
    Su, Guosheng
    Lund, Mogens Sandro
    Karaman, Emre
    JOURNAL OF DAIRY SCIENCE, 2022, 105 (03) : 2426 - 2438