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
Estimating Effects and Making Predictions from Genome-Wide Marker Data
TL;DR: In this article, an integrated approach to the estimation of the SNP effects and to the prediction of trait values, treating SNP effects as random instead of fixed effects, is proposed, which is a property of the estimator.
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Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population
Hongding Gao,Hongding Gao,Ole F. Christensen,Per Madsen,U. S. Nielsen,Yuan Zhang,Mogens Sandø Lund,Guosheng Su +7 more
TL;DR: The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle and can be improved by adjusting the scale of the genomic relationship matrix.
Journal ArticleDOI
Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding
Dario Grattapaglia,Orzenil B. Silva-Junior,Orzenil B. Silva-Junior,Rafael Tassinari Resende,Eduardo P. Cappa,Bárbara S. F. Müller,Bárbara S. F. Müller,Biyue Tan,Fikret Isik,Blaise Ratcliffe,Yousry A. El-Kassaby +10 more
TL;DR: Genomic selection has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values, and areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios.
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Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters.
Kyall R. Zenger,Mehar S. Khatkar,David B. Jones,Nima Khalilisamani,Nima Khalilisamani,Dean R. Jerry,Herman W. Raadsma,Herman W. Raadsma +7 more
TL;DR: The technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries are discussed, with a particular focus on molluscs and marine shrimp.
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Genomic predictions for New Zealand dairy bulls and integration with national genetic evaluation
B.L. Harris,D. L. Johnson +1 more
TL;DR: A method is described for the prediction of breeding values incorporating genomic information that combines genomic predictions with traditional ancestral information lost between the process of deregression of the national breeding values and subsequent re-estimation using the genomic relationship matrix.
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.