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Performance Of Genomic Selection In Mice
A. Legarra, C. Robert-Granié, E. Manfredi, J. Elsen
Published 2008 · Biology, Medicine
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Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as “genomic selection.” There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http://gscan.well.ox.ac.uk/), including 1884 individuals and 10,946 SNP markers. We used linear mixed models, using extensions of association analysis. Cross-validation techniques were used, providing assumption-free estimates of predictive ability. Sampling of validation and training data sets was carried out across and within families, which allows comparing across- and within-family information. Use of genomewide genetic markers increased predictive ability up to 0.22 across families and up to 0.03 within families. The latter is not statistically significant. These values are roughly comparable to increases of up to 0.57 (across family) and 0.14 (within family) in accuracy of prediction of genetic value. In this data set, within-family information was more accurate than across-family information, and populational linkage disequilibrium was not a completely accurate source of information for genetic evaluation. This fact questions some applications of genomic selection.
This paper references
Equivalent Linear Models to Reduce Computations
C. Henderson (1985)
Bayesian Methods in Animal Breeding Theory
D. Gianola (1986)
Genetics for the Animal Sciences
L. D. V. Vleck (1987)
Genetics for the Animal Sciences. W. H. Freeman
Van Vleck (1987)
Marker assisted selection using best linear unbiased prediction
R. Fernando (1989)
Efficiency of marker-assisted selection in the improvement of quantitative traits.
R. Lande (1990)
Subset Selection in Regression.
G. Raab (1991)
Subset Selection in Regression
A. Atkinson (1992)
Genetics and analysis of quantitative traits
W. Ewens (1999)
Nonparametric simple regression
J. Fox (2000)
A method for fine mapping quantitative trait loci in outbred animal stocks.
R. Mott (2000)
Quantitative trait loci mapping in F(2) crosses between outbred lines.
M. Pérez-Enciso (2000)
Prediction of total genetic value using genome-wide dense marker maps.
T. Meuwissen (2001)
Multifactorial genetics: The use of molecular genetics in the improvement of agricultural populations
J. Dekkers (2002)
Analysis of genetic diversity for the management of conserved subdivided populations. Conserv
A Caballero (2002)
Incorporating molecular information in breeding programmes: methodology.
R. Fernando (2003)
Analysis of genetic diversity for the management of conserved subdivided populations
A. Caballero (2004)
Benefits from marker-assisted selection under an additive polygenic genetic model.
B. Villanueva (2005)
A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice
L. Solberg (2005)
Finding the molecular basis of complex genetic variation in humans and mice
R. Mott (2006)
Genomic-Assisted Prediction of Genetic Value With Semiparametric Procedures
D. Gianola (2006)
Importance and implementation of molecular markers in selective breeding programs for aquaculture species.
V. Martinez (2006)
Estimation of Breeding Values of Inbred Lines using Best Linear Unbiased Prediction (BLUP) and Genetic Similarities
A. M. Bauer (2006)
Assumption-Free Estimation of Heritability from Genome-Wide Identity-by-Descent Sharing between Full Siblings
P. Visscher (2006)
Strategy for applying genome-wide selection in dairy cattle.
L. Schaeffer (2006)
Testing marker assisted selection in a real breeding program.
A. Chamberlain (2006)
Genome-wide genetic association of complex traits in heterogeneous stock mice
W. Valdar (2006)
A unified mixed-model method for association mapping that accounts for multiple levels of relatedness
J. Yu (2006)
Implementation of marker-assisted selection: practical lessons from dairy cattle
D. Boichard (2006)
Genetic and Environmental Effects on Complex Traits in Mice
W. Valdar (2006)
Marker-assisted selection for commercial crossbred performance.
J. Dekkers (2007)
Genomic selection for marker-assisted improvement in line crosses
N. Piyasatian (2007)
A comparison of different regression methods for genomic-assisted prediction of genetic values in dairy cattle
G. Moser (2007)
The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values
D. Habier (2007)
Proceedings of the 58th Annual Meeting of the European Association for Animal Production
Short communication: correlations of marker-assisted breeding values with progeny-test breeding values for eight hundred ninety-nine French Holstein bulls.
F. Guillaume (2008)
Technical note: Computing strategies in genome-wide selection.
A. Legarra (2008)
Genome-wide selection computing strategies
A Legarra (2008)
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