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
CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses.
TL;DR: A genome-based restricted maximum likelihood, CORE GREML, is described, which estimates covariance between random effects, a key parameter for estimation, especially when partitioning phenotypic variance by multi-omics layers.
Journal ArticleDOI
Genome scan for postmortem carcass traits in Nellore cattle.
G. A. Fernandes Júnior,Raphael Bermal Costa,G. M. F. de Camargo,Roberto Carvalheiro,Guilherme J. M. Rosa,Fernando Baldi,D. A. Garcia,Daniel Gustavo Mansan Gordo,Rafael Espigolan,Luciana Takada,Ana Fabrícia Braga Magalhães,Tiago Bresolin,Fabieli Loise Braga Feitosa,Luis Artur Loyola Chardulo,H. N. de Oliveira,L. G. de Albuquerque +15 more
TL;DR: Several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle are identified and can be helpful for further functional genomic studies.
Journal ArticleDOI
Genome-wide association study of yield components and fibre quality traits in a cotton germplasm diversity panel
Washington J. Gapare,Warren C. Conaty,Qian-Hao Zhu,Shiming Liu,Warwick N. Stiller,Danny J. Llewellyn,Iain W. Wilson +6 more
TL;DR: Whole genome sequencing combined with whole genomic selection approaches that do not require prior knowledge about the effect or function of individual SNPs may be better suited than GWAS for trait dissection and prediction in cotton breeding.
Book ChapterDOI
QTL mapping using high-throughput sequencing.
TL;DR: Modifications of the traditional biparental mapping population that provide higher resolution of QTL positions, QTL fine-mapping procedures, and genome-wide association studies are discussed, all of which are greatly facilitated by high-throughput sequencing methods.
Journal ArticleDOI
MoBPS - Modular Breeding Program Simulator
TL;DR: The R-package MoBPS provides pre-implemented functions for common breeding practices such as optimum genetic contributions and single-step GBLUP but also allows the user to replace certain steps with personalized and/or self-written solutions.
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.