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
Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).
TL;DR: Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity, and Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date.
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Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations
Jose Luis Gualdron Duarte,Rodolfo Juan Carlos Cantet,Ronald O. Bates,Catherine W. Ernst,Nancy E. Raney,Juan P. Steibel +5 more
TL;DR: The standardized test of marker effects using their own variance helps in detecting specific genomic regions involved in the additive variance, and in reducing false positives.
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Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
TL;DR: Most of the additive genetic variance for the traits in the Nordic Holstein population can be explained using 44 K informative SNP markers.
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Genome-wide association study identifies three key loci for high mesocarp oil content in perennial crop oil palm.
Chee Keng Teh,Ai-Ling Ong,Qi Bin Kwong,Sukganah Apparow,Fook Tim Chew,Sean Mayes,Mohaimi Mohamed,David Ross Appleton,Harikrishna Kulaveerasingam +8 more
TL;DR: This work performed GWAS for oil-to-dry-mesocarp content (O/DM) on 2,045 genotyped tenera palms using 200K SNPs that were selected based on the short-range linkage disequilibrium distance, which is inherent with long breeding cycles and heterogeneous breeding populations.
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The genetic architecture of teosinte catalyzed and constrained maize domestication
Chin Jian Yang,Luis Fernando Samayoa,Peter J. Bradbury,Bode A. Olukolu,Wei Xue,Alessandra M. York,Michael R. Tuholski,Weidong Wang,Lora L. Daskalska,Michael A. Neumeyer,José de Jesús Sánchez-González,Maria Cinta Romay,Jeffrey C. Glaubitz,Qi Sun,Edward S. Buckler,James B. Holland,John Doebley +16 more
TL;DR: A strong, nonneutral divergence is identified between teosinte and maize landrace genetic variance–covariance matrices (G-matrices), which indicates that the degree of constraint is more unfavorable for further evolution along the same trajectory.
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.