Efficient Methods to Compute Genomic Predictions
TLDR
Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously, and a blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects.About:
This article is published in Journal of Dairy Science.The article was published on 2008-11-01 and is currently open access. It has received 4196 citations till now. The article focuses on the topics: Best linear unbiased prediction & Allele frequency.read more
Citations
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Journal ArticleDOI
The effects of training population design on genomic prediction accuracy in wheat
Stefan M Edwards,Jaap B. Buntjer,Robert Jackson,Alison R. Bentley,Jacob Lage,Ed Byrne,C. Burt,Peter Jack,Simon Berry,Edward Flatman,Bruno Poupard,Stephen Smith,Charlotte Hayes,Gaynor Rc,Gregor Gorjanc,Phil Howell,Eric S. Ober,Ian Mackay,John M. Hickey +18 more
TL;DR: The results of this study emphasise the importance of the training panel design in relation to the genetic material to which the resulting prediction model is to be applied, and the design of training sets is in turn central to achieving sufficient levels of accuracy.
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Utility of whole-genome sequence data for across-breed genomic prediction
Biaty Raymond,Aniek C. Bouwman,Chris Schrooten,Jeanine J. Houwing-Duistermaat,Jeanine J. Houwing-Duistermaat,Roel F. Veerkamp +5 more
TL;DR: The results demonstrated that the accuracy of across-breed GP can be improved by using markers that are pre-selected from WGS based on their potential causal effect, and showed that simply increasing the number of markers up to the WGS level does not increase the accuracy.
Journal ArticleDOI
Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review.
TL;DR: The use of genomic selection can decrease cycle time and costs in hybrid breeding, particularly by rapidly establishing heterotic pools, reducing testcrossing, and limiting the loss of genetic variance as discussed by the authors.
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Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.
Bárbara S. F. Müller,Bárbara S. F. Müller,Bárbara S. F. Müller,Leandro G. Neves,Janeo Eustáquio de Almeida Filho,Marcio F. R. Resende,Patricio R. Munoz,Paulo Eduardo Telles dos Santos,Estefano Paludzyszyn Filho,Matias Kirst,Dario Grattapaglia,Dario Grattapaglia +11 more
TL;DR: This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection.
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A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships.
TL;DR: This work derives the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation.
References
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Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
TL;DR: 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.
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Coefficients of Inbreeding and Relationship
TL;DR: The importance of having a coefficient by means of which the degree of inbreeding may be expressed has been brought out by Pearl' in a number of papers published between 1913 and 1917.
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Strategy for applying genome-wide selection in dairy cattle.
TL;DR: Genome-wide selection may become a popular tool for genetic improvement in livestock after a strategy that utilizes these advantages was compared with a traditional progeny testing strategy under a typical Canadian-like dairy cattle situation.
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Derivation, calculation, and use of national animal model information.
Paul M. VanRaden,G.R. Wiggans +1 more
TL;DR: New terms and definitions were developed to explain national USDA genetic evaluations computed by an animal model, whereiability is the squared correlation of predicted and true transmitting ability.
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Accuracy of Genomic Selection Using Different Methods to Define Haplotypes
TL;DR: It was concluded that genomic selection is considerably more accurate than traditional selection, especially for a low-heritability trait.