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
Assessing accuracy of imputation using different SNP panel densities in a multi-breed sheep population
Ricardo Vieira Ventura,Stephen P. Miller,Stephen P. Miller,Ken G. Dodds,Benoit Auvray,Michael Lee,Matthew J. Bixley,Shannon M. Clarke,John C. McEwan +8 more
TL;DR: A method is presented that predicts imputation accuracy for individual animals at the low-density level, before running imputation, which can be used to restrict genomic prediction only to the animals that can be imputed with sufficient accuracy.
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Inbreeding and purging at the genomic Level: the Chillingham cattle reveal extensive, non-random SNP heterozygosity.
John L. Williams,Stephen J. G. Hall,M. Del Corvo,Keith T. Ballingall,Licia Colli,P. Ajmone Marsan,Filippo Biscarini +6 more
TL;DR: High-density SNP genotyping with the 777K SNP chip showed that 9.1% of loci on the chip are polymorphic in the herd, compared with 62-90% seen in commercial cattle breeds, suggesting that some loci are under balancing selection.
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Enhancing genome-enabled prediction by bagging genomic BLUP.
TL;DR: It was found that bagging can ameliorate predictive performance of GBLUP and make it more robust against over-fitting, and quantify candidate-specific cross-validation uncertainty was proposed and assessed.
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Breeding Value of Primary Synthetic Wheat Genotypes for Grain Yield.
Jafar Jafarzadeh,David Bonnett,Jean-Luc Jannink,Deniz Akdemir,Susanne Dreisigacker,Mark E. Sorrells +5 more
TL;DR: To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes were crossed to 20 spring bread wheat cultivars at the International Wheat and Maize Improvement Center in Ciudad Obregon, Mexico.
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Accuracy of genomic prediction for milk production traits in the Chinese Holstein population using a reference population consisting of cows
Xiangdong Ding,Zhe Zhang,Zhe Zhang,X. Li,Sheng Wang,Xiaoping Wu,Dongxiao Sun,Ying Yu,Jianfeng Liu,Y. Wang,Yunhai Zhang,Suxia Zhang,Qiong Zhang +12 more
TL;DR: The results indicate that, as an alternative, genomic selection using cows in the reference population is feasible and theoretical accuracy of genomic prediction in Chinese Holstein is higher than the accuracies of conventional pedigree index.
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.