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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The unified approach to the use of genomic and pedigree information in genomic evaluations revisited
TL;DR: The LDLAb method was demonstrated to be a unified approach that maximized accuracy of GEBV compared to previous methodologies and removed the bias in the GEBK, and demonstrates how to make best use the marker information.
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Accuracy of genotype imputation in Nelore cattle
Roberto Carvalheiro,Solomon Antwi Boison,Haroldo H. R. Neves,Mehdi Sargolzaei,Flavio S Schenkel,Yuri Tani Utsunomiya,Ana M. Pérez O'Brien,Johann Sölkner,John C. McEwan,Curtis P. Van Tassell,Tad S. Sonstegard,José Fernando Garcia +11 more
TL;DR: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute.
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Incorporation of causative quantitative trait nucleotides in single-step GBLUP
TL;DR: Whether ssGBLUP is useful for genomic prediction when some or all QTN are known is investigated, and single-step GBLUP can account for causative QTN via a weighted GRM.
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Accuracy of Whole-Genome Prediction Using a Genetic Architecture-Enhanced Variance-Covariance Matrix
Zhe Zhang,Zhe Zhang,Malena Erbe,Jinlong He,Ulrike Ober,Ning Gao,Hao Zhang,Henner Simianer,Jiaqi Li +8 more
TL;DR: Predictive ability and difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T and G matrices, which is mainly due to the increased similarity between the trait-specific relationship matrix (T matrix) and the genetic relationship matrix at unobserved causal loci.
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Genomic prediction for grain zinc and iron concentrations in spring wheat
Govindan Velu,José Crossa,Ravi P. Singh,Yuanfeng Hao,Susanne Dreisigacker,Paulino Pérez-Rodríguez,Arun Kumar Joshi,Ravish Chatrath,Vikas Gupta,Arun Balasubramaniam,Chhavi Tiwari,V. K. Mishra,Virinder Singh Sohu,G. S. Mavi +13 more
TL;DR: Predictability estimated through cross-validation approach showed moderate to high level; hence, genomic selection approach holds great potential for biofortification breeding to enhance grain zinc and iron concentrations in wheat.
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.