Comparison of a single-step with a multistep single nucleotide polymorphism best linear unbiased predictor model for genomic evaluation of conformation traits in German Holsteins

被引:7
|
作者
Alkhoder, H. [1 ]
Liu, Z. [1 ]
Segelke, D. [1 ]
Reents, R. [1 ]
机构
[1] IT Solut Anim Prod Vit, Heinrich Schroeder Weg 1, D-27283 Verden, Germany
关键词
single-step model; single nucleotide polymorphism best linear unbiased predictor model; conformation trait; dairy cattle; PEDIGREE; BIAS;
D O I
10.3168/jds.2021-21145
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Genomic evaluation based on a single-step model uses all available data of phenotype, genotype, and pedigree; therefore, it should provide unbiased genomic breeding values with a higher correlation of prediction than the current multistep genomic model. Since 2019, a mixed reference population of cows and bulls has been applied to the routine multistep genomic evaluation in German Holsteins. For a fair comparison between the single-step and multistep genomic models, the same phenotype, genotype, and pedigree data were used. Because of its simple structure of the standard multitrait animal model used for German Holstein conventional evaluation, conformation traits were chosen as the first trait group to test a single-step SNP BLUP model for the large, genotyped population of German Holsteins. Genotype, phenotype, and pedigree data were taken from the official August 2020 conventional and genomic evaluation. Because of the same trait definition in national and multiple across-country evaluation for the conformation traits, deregressed multiple across country evaluation estimated breeding value (EBV) of foreign bulls were treated as a new source of data for the same trait in the genomic evaluations. Due to a short history of female genotyping in Germany, the last 3 yr of youngest cows and bulls were deleted, instead of 4 yr, to perform a genomic validation. In comparison to the multistep genomic model, the single-step SNP BLUP model resulted in a higher correlation and greater variance of genomic EBV according to 798 national validation bulls. The regression of genomic prediction of the current, full evaluation on the earlier, truncated evaluation was slightly closer to 1 than the multistep model. For the validation bulls or youngest genomic artificial insemination bulls, correlation of genomic EBV between the 2 models was, on average, 0.95 across all the conformation traits. We did not find overprediction of young animals by the single-step SNP BLUP model for the conformation traits in German Holsteins.
引用
收藏
页码:3306 / 3322
页数:17
相关论文
共 50 条
  • [1] Application of single-step single nucleotide polymorphism best linear unbiased predictor model with unknown-parent groups for type traits in Japanese Holsteins
    Osawa, Takefumi
    Masuda, Yutaka
    Saburi, Junichi
    Hirumachi, Keita
    JOURNAL OF DAIRY SCIENCE, 2023, 106 (07) : 4847 - 4859
  • [2] Technical note: Genetic groups in single-step single nucleotide polymorphism best linear unbiased predictor
    Vandenplas, Jeremie
    Eding, Herwin
    Calus, Mario P. L.
    JOURNAL OF DAIRY SCIENCE, 2021, 104 (03) : 3298 - 3303
  • [3] Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals
    Masuda, Y.
    Misztal, I.
    Tsuruta, S.
    Legarra, A.
    Aguilar, I.
    Lourenco, D. A. L.
    Fragomeni, B. O.
    Lawlor, T. J.
    JOURNAL OF DAIRY SCIENCE, 2016, 99 (03) : 1968 - 1974
  • [4] Comparison of Algorithms for Approximation of Accuracies for Single-Step Genomic Best Linear Unbiased Predictor Models
    Ramos, Pedro Vital Brasil
    Garcia, Andre
    Retallick, Kelli J.
    Bermann, Matias
    Misztal, Ignacy
    Lourenco, Daniela
    JOURNAL OF ANIMAL SCIENCE, 2023, 101
  • [5] Comparison of Algorithms for Approximation of Accuracies for Single-Step Genomic Best Linear Unbiased Predictor Models
    Ramos, Pedro Vital Brasil
    Garcia, Andre
    Retallick, Kelli J.
    Bermann, Matias
    Misztal, Ignacy
    Lourenco, Daniela
    JOURNAL OF ANIMAL SCIENCE, 2023, 101 : 16 - 17
  • [6] Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus
    Lourenco, D. A. L.
    Tsuruta, S.
    Fragomeni, B. O.
    Masuda, Y.
    Aguilar, I.
    Legarra, A.
    Bertrand, J. K.
    Amen, T. S.
    Wang, L.
    Moser, D. W.
    Misztal, I.
    JOURNAL OF ANIMAL SCIENCE, 2015, 93 (06) : 2653 - 2662
  • [7] Single-step genomic evaluation for linear conformation and performance traits for German riding horses
    Wobbe, Mirell
    Alkhoder, Hatem
    Liu, Zengting
    Vosgerau, Sarah
    Krat-Tenmacher, Nina
    Prondzinski, Mario Von Depka
    Kalm, Ernst
    Reents, Reinhard
    Nolte, Wietje
    Kuehn, Christa
    Tetens, Jens
    Thaller, Georg
    Stock, Kathrin F.
    ZUCHTUNGSKUNDE, 2022, 94 (05): : 363 - 379
  • [8] Multibreed genomic evaluation for production traits of dairy cattle in the United States using single-step genomic best linear unbiased predictor
    Cesarani, A.
    Lourenco, D.
    Tsuruta, S.
    Legarra, A.
    Nicolazzi, E. L.
    VanRaden, P. M.
    Misztal, I
    JOURNAL OF DAIRY SCIENCE, 2022, 105 (06) : 5141 - 5152
  • [9] Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Holstein cattle
    Guarini, A. R.
    Lourenco, D. A. L.
    Brito, L. F.
    Sargolzaei, M.
    Baes, C. F.
    Miglior, F.
    Misztal, I.
    Schenkel, F. S.
    JOURNAL OF DAIRY SCIENCE, 2018, 101 (09) : 8076 - 8086
  • [10] Alternative SNP weighting for single-step genomic best linear unbiased predictor evaluation of stature in US Holsteins in the presence of selected sequence variants
    Fragomeni, B. O.
    Lourenco, D. A. L.
    Legarra, A.
    VanRaden, P. M.
    Misztal, I
    JOURNAL OF DAIRY SCIENCE, 2019, 102 (11) : 10012 - 10019