The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes

Title
The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes
Publication Date
2012
Author(s)
Clark, Sam A
( author )
OrcID: https://orcid.org/0000-0001-8605-1738
Email: sclark37@une.edu.au
UNE Id une-id:sclark37
Hickey, J
Daetwyler, H D
Van Der Werf, Julius H
( author )
OrcID: https://orcid.org/0000-0003-2512-1696
Email: jvanderw@une.edu.au
UNE Id une-id:jvanderw
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
BioMed Central Ltd
Place of publication
United Kingdom
DOI
10.1186/1297-9686-44-4
UNE publication id
une:12726
Abstract
Background: The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values. Methods: Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated. Results: The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy.
Link
Citation
Genetics Selection Evolution, v.44, p. 1-9
ISSN
1297-9686
0999-193X
Start page
1
End page
9

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