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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Cow genotyping strategies for genomic selection in a small dairy cattle population
Janez Jenko,G.R. Wiggans,T.A. Cooper,Sophie Eaglen,W.g. De L. Luff,M. Bichard,Ricardo Pong-Wong,John Woolliams +7 more
TL;DR: It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach.
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Improving genomic prediction of growth and wood traits in Eucalyptus using phenotypes from non-genotyped trees by single-step GBLUP.
Eduardo P. Cappa,Eduardo P. Cappa,Bruno Marco de Lima,Orzenil B. Silva-Junior,Carla Garcia,Shawn D. Mansfield,Dario Grattapaglia +6 more
TL;DR: It is concluded that ssGBLUP is a promising breeding tool to improve accuracies and bias over classical GBLUP for genomic evaluation in Eucalyptus breeding practice.
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A comparison of genomic selection methods for breeding value prediction
Xin Wang,Zefeng Yang,Chenwu Xu +2 more
TL;DR: This study showed that the genetic architecture of a trait should be fully considered when a GS method is chosen, and RR-BLUP slightly outperformed the others in both simulated scenarios and real data analysis, thus demonstrating its robustness and indicating that it was quite effective in this case.
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Evaluating Methods of Updating Training Data in Long-Term Genomewide Selection.
TL;DR: The results suggest that an optimal method of updating the training population is also very practical, as a breeder might desire to gather phenotypic data on lines predicted to be the best, perhaps to evaluate possible cultivars.
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Invited review: Beef-on-dairy-The generation of crossbred beef × dairy cattle.
TL;DR: In this article, the authors compare the performance of dairy and beef matings and find that dairy females exhibit greater genetic variability than beef females, which implies that "one size fits all" may not be appropriate for bull selection.
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.