Accelerating improvement of livestock with genomic selection

Meuwissen, Theo, Hayes, Ben and Goddard, Mike (2013) Accelerating improvement of livestock with genomic selection. Annual Review of Animal Biosciences, 1 221-237. doi:10.1146/annurev-animal-031412-103705

Author Meuwissen, Theo
Hayes, Ben
Goddard, Mike
Title Accelerating improvement of livestock with genomic selection
Journal name Annual Review of Animal Biosciences   Check publisher's open access policy
ISSN 2165-8110
Publication date 2013-01
Sub-type Article (original research)
DOI 10.1146/annurev-animal-031412-103705
Open Access Status Not yet assessed
Volume 1
Start page 221
End page 237
Total pages 17
Place of publication Palo Alto, CA, United States
Publisher Annual Reviews
Language eng
Abstract 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.
Keyword Complex traits
Genetic improvement
Marker-assisted selection
Use of genome sequence data
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
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Citation counts: TR Web of Science Citation Count  Cited 40 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 42 times in Scopus Article | Citations
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