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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Genomic selection in maritime pine.
Fikret Isik,Jérôme Bartholomé,Alfredo E. Farjat,Emilie Chancerel,Annie Raffin,Leopoldo Sanchez,Christophe Plomion,Laurent Bouffier +7 more
TL;DR: The sensitivity analysis suggested that prior densities (variance explained by markers) had little or no discernible effect on posterior means (residual variance) in Bayesian prediction models.
Adding Genetically Distant Individualsto Training Populations Reduces GenomicPrediction Accuracy in Barley
Aaron J. Lorenz,Kevin P. Smith +1 more
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Imputation of high-density genotypes in the Fleckvieh cattle population
TL;DR: Genotyping key animals at high density and subsequent population-based genotype imputation yield high imputation accuracy, even when the reference population is small.
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Genomic Prediction of Single Crosses in the Early Stages of a Maize Hybrid Breeding Pipeline
TL;DR: The results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.
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Genomic prediction of genetic values for resistance to wheat rusts
Leonardo Ornella,Sukhwinder Singh,Paulino Pérez,Juan Burgueño,Ravi P. Singh,Elizabeth Tapia,Sridhar Bhavani,Susanne Dreisigacker,Hans-Joachim Braun,Ky L. Mathews,José Crossa +10 more
TL;DR: In this article, five CIMMYT wheat populations evaluated for resistance were used to predict resistance to stem rust and yellow rust using Bayesian least absolute shrinkage and selection operator (LASSO) (BL), ridge regression (RR), and support vector regression with linear or radial basis function kernel models.
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.