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
Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary U.S. Holstein cows
John B. Cole,G.R. Wiggans,Li Ma,Tad S. Sonstegard,T.J. Lawlor,Brian A Crooker,Curtis P. Van Tassell,Jing Yang,Shengwen Wang,Lakshmi K. Matukumalli,Yang Da +10 more
TL;DR: A genome-wide analysis of predicted transmitting ability (PTA) of 31 production, health, reproduction and body conformation traits in contemporary Holstein cows provides useful information for annotating phenotypic effects on the dairy genome and for building consensus of dairy QTL effects.
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Po-Ru Loh,Brendan Bulik-Sullivan,Bjarni J. Vilhjálmsson,Rany M. Salem,Daniel I. Chasman,Paul M. Ridker,Benjamin M. Neale,Nick Patterson,Alkes L. Price,George Tucker,Hilary K. Finucane,Bonnie Berger Leighton +11 more
TL;DR: BOLT-LMM is presented, which requires only a small number of O(MN) iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes.
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Perspectives for Genomic Selection Applications and Research in Plants
TL;DR: How genomic pre-diction can be integrated into breeding efforts is described and achievements and areas where more research is needed are pointed out.
Journal ArticleDOI
Bias in genomic predictions for populations under selection.
TL;DR: The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities.
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The Genetic Architecture of Maize Height
Jason A. Peiffer,Maria Cinta Romay,Michael A. Gore,Sherry Flint-Garcia,Sherry Flint-Garcia,Zhiwu Zhang,Mark J. Millard,Mark J. Millard,Candice Gardner,Candice Gardner,Michael D. McMullen,Michael D. McMullen,James B. Holland,James B. Holland,Peter J. Bradbury,Edward S. Buckler,Edward S. Buckler +16 more
TL;DR: In this paper, the authors measured the plant height, ear height, flowering time, and node counts of plants grown in.64,500 plots across 13 environments and found that maize height was under strong genetic control and had a highly polygenic genetic architecture.
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.