Accelerating Improvement of Livestock with Genomic Selection

被引:227
|
作者
Meuwissen, Theo [1 ]
Hayes, Ben [2 ]
Goddard, Mike [3 ]
机构
[1] Norwegian Univ Life Sci, Dept Anim & Aquaculture Sci, N-1430 As, Norway
[2] Dept Primary Ind, Biosci Res Div, Bundoora, Vic 3083, Australia
[3] Univ Melbourne, Melbourne Sch Land & Environm, Melbourne, Vic 3010, Australia
关键词
marker-assisted selection; genetic improvement; complex traits; use of genome sequence data; GENETIC-RELATIONSHIP INFORMATION; MARKER ASSISTED SELECTION; DAIRY-CATTLE; BREEDING VALUES; RELATIONSHIP MATRIX; COMPLEX TRAITS; FULL PEDIGREE; MILK-YIELD; PREDICTION; ACCURACY;
D O I
10.1146/annurev-animal-031412-103705
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Three recent breakthroughs have resulted in the current widespread use of DNA information: the genomic selection (GS) methodology, which is a form of marker-assisted selection on a genome-wide scale, and the discovery of large numbers of single-nucleotide markers and cost effective methods to genotype them. GS estimates the effect of thousands of DNA markers simultaneously. Nonlinear estimation methods yield higher accuracy, especially for traits with major genes. The marker effects are estimated in a genotyped and phenotyped training population and are used for the estimation of breeding values of selection candidates by combining their genotypes with the estimated marker effects. The benefits of GS are greatest when selection is for traits that are not themselves recorded on the selection candidates before they can be selected. In the future, genome sequence data may replace SNP genotypes as markers. This could increase GS accuracy because the causative mutations should be included in the data.
引用
收藏
页码:221 / 237
页数:17
相关论文
共 50 条
  • [41] Genomic selection for marker-assisted improvement in line crosses
    Piyasatian, N.
    Fernando, R. L.
    Dekkers, J. C. M.
    THEORETICAL AND APPLIED GENETICS, 2007, 115 (05) : 665 - 674
  • [42] Optimizing genomic selection in soybean: An important improvement in agricultural genomics
    Yoosefzadeh-Najafabadi, Mohsen
    Rajcan, Istvan
    Eskandari, Milad
    HELIYON, 2022, 8 (11)
  • [43] Multi-trait Genomic Selection Methods for Crop Improvement
    Moeinizade, Saba
    Kusmec, Aaron
    Hu, Guiping
    Wang, Lizhi
    Schnable, Patrick S.
    GENETICS, 2020, 215 (04) : 931 - 945
  • [44] Genomic screening for artificial selection during domestication and improvement in maize
    Yamasaki, Masanori
    Wright, Stephen I.
    Mcmullen, Michael D.
    ANNALS OF BOTANY, 2007, 100 (05) : 967 - 973
  • [45] Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs
    Jonas, Elisabeth
    de Koning, Dirk-Jan
    FRONTIERS IN GENETICS, 2015, 6
  • [46] Improvement of Genomic Predictions in Small Breeds by Construction of Genomic Relationship Matrix Through Variable Selection
    Mancin, Enrico
    Mota, Lucio Flavio Macedo
    Tuliozi, Beniamino
    Verdiglione, Rina
    Mantovani, Roberto
    Sartori, Cristina
    FRONTIERS IN GENETICS, 2022, 13
  • [47] GENETICS OF LIVESTOCK IMPROVEMENT
    PHILLIPS, RW
    QUARTERLY REVIEW OF BIOLOGY, 1965, 40 (03): : 290 - &
  • [48] Improvement of Livestock Husbandry
    Lange, Doris
    TIERAERZTLICHE UMSCHAU, 2012, 67 (09) : 370 - 372
  • [49] Genetic and genomic resources, and breeding for accelerating improvement of small millets: current status and future interventions
    M. Vetriventhan
    Vania C. R. Azevedo
    H. D. Upadhyaya
    A. Nirmalakumari
    Joanna Kane-Potaka
    S. Anitha
    S. Antony Ceasar
    M. Muthamilarasan
    B. Venkatesh Bhat
    K. Hariprasanna
    Amasiddha Bellundagi
    Deepika Cheruku
    C. Backiyalakshmi
    Dipak Santra
    C. Vanniarajan
    Vilas A. Tonapi
    The Nucleus, 2020, 63 : 217 - 239
  • [50] Genetic and genomic resources, and breeding for accelerating improvement of small millets: current status and future interventions
    Vetriventhan, M.
    Azevedo, Vania C. R.
    Upadhyaya, H. D.
    Nirmalakumari, A.
    Kane-Potaka, Joanna
    Anitha, S.
    Ceasar, S. Antony
    Muthamilarasan, M.
    Bhat, B. Venkatesh
    Hariprasanna, K.
    Bellundagi, Amasiddha
    Cheruku, Deepika
    Backiyalakshmi, C.
    Santra, Dipak
    Vanniarajan, C.
    Tonapi, Vilas A.
    NUCLEUS-INDIA, 2020, 63 (03): : 217 - 239