Using the genomic relationship matrix to predict the accuracy of genomic selection

Goddard, M. E., Hayes, B. J. and Meuwissen, T. H. E. (2011) Using the genomic relationship matrix to predict the accuracy of genomic selection. Journal of Animal Breeding and Genetics, 128 6: 409-421. doi:10.1111/j.1439-0388.2011.00964.x

Author Goddard, M. E.
Hayes, B. J.
Meuwissen, T. H. E.
Title Using the genomic relationship matrix to predict the accuracy of genomic selection
Journal name Journal of Animal Breeding and Genetics   Check publisher's open access policy
ISSN 0931-2668
Publication date 2011-12
Sub-type Article (original research)
DOI 10.1111/j.1439-0388.2011.00964.x
Open Access Status Not yet assessed
Volume 128
Issue 6
Start page 409
End page 421
Total pages 13
Place of publication Berlin, Germany
Publisher Wiley-Blackwell
Language eng
Abstract Estimated breeding values (EBVs) using data from genetic markers can be predicted using a genomic relationship matrix, derived from animal's genotypes, and best linear unbiased prediction. However, if the accuracy of the EBVs is calculated in the usual manner (from the inverse element of the coefficient matrix), it is likely to be overestimated owing to sampling errors in elements of the genomic relationship matrix. We show here that the correct accuracy can be obtained by regressing the relationship matrix towards the pedigree relationship matrix so that it is an unbiased estimate of the relationships at the QTL controlling the trait. This method shows how the accuracy increases as the number of markers used increases because the regression coefficient (of genomic relationship towards pedigree relationship) increases. We also present a deterministic method for predicting the accuracy of such genomic EBVs before data on individual animals are collected. This method estimates the proportion of genetic variance explained by the markers, which is equal to the regression coefficient described above, and the accuracy with which marker effects are estimated. The latter depends on the variance in relationship between pairs of animals, which equals the mean linkage disequilibrium over all pairs of loci. The theory was validated using simulated data and data on fat concentration in the milk of Holstein cattle.
Keyword Genomic selection
Relationship matrix
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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