Prediction of total genetic value using genome-wide dense marker maps

Meuwissen, T. H. E., Hayes, B. J. and Goddard, M. E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157 4: 1819-1829.

Author Meuwissen, T. H. E.
Hayes, B. J.
Goddard, M. E.
Title Prediction of total genetic value using genome-wide dense marker maps
Journal name Genetics   Check publisher's open access policy
ISSN 0016-6731
1943-2631
Publication date 2001-04-01
Sub-type Article (original research)
Open Access Status Not yet assessed
Volume 157
Issue 4
Start page 1819
End page 1829
Total pages 11
Place of publication Bethesda, MD, United States
Publisher Genetics Society of America
Language eng
Formatted abstract
Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ~50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be
estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
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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