Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps T. H. E. Meuwissen a , B. J. Hayes b , and M. E. Goddard b,c a Research Institute of Animal Science and Health, 8200 AB Lelystad, The Netherlands, b Victorian Institute of Animal Science, Attwood 3049, Victoria, Australia c Institute of Land and Food Resources, University of Melbourne, Parkville 3052, Victoria, Australia Corresponding author: T. H. E. Meuwissen, Department of Animal Breeding and Genetics, DLO-Institute for Animal Science and Health, Box 65, 8200 AB Lelystad, The Netherlands., t.h.e.meuwissen@id.dlo.nl (E-mail) Communicating editor: C. H ALEY 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 (N e = 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Genetics Genetics Society of America

Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

Genetics, Volume 157 (4): 1819 – Apr 1, 2001

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Publisher
Genetics Society of America
Copyright
Copyright © 2001 by the Genetics Society of America
ISSN
0016-6731
eISSN
1943-2631
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Abstract

T. H. E. Meuwissen a , B. J. Hayes b , and M. E. Goddard b,c a Research Institute of Animal Science and Health, 8200 AB Lelystad, The Netherlands, b Victorian Institute of Animal Science, Attwood 3049, Victoria, Australia c Institute of Land and Food Resources, University of Melbourne, Parkville 3052, Victoria, Australia Corresponding author: T. H. E. Meuwissen, Department of Animal Breeding and Genetics, DLO-Institute for Animal Science and Health, Box 65, 8200 AB Lelystad, The Netherlands., t.h.e.meuwissen@id.dlo.nl (E-mail) Communicating editor: C. H ALEY 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 (N e = 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.

Journal

GeneticsGenetics Society of America

Published: Apr 1, 2001

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