Accelerating Improvement of Livestock with Genomic Selection

被引:228
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
来源
ANNUAL REVIEW OF ANIMAL BIOSCIENCES, VOL 1 | 2013年 / 1卷
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
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