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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Using genomics to enhance selection of novel traits in North American dairy cattle.
TL;DR: Progress in the genetic evaluation of novel traits in Canada and the United States is reviewed, methods to predict selection accuracy based on cow reference populations are assessed, and how the use of indicator traits could increase genomic selection accuracy is illustrated.
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Selinene Volatiles Are Essential Precursors for Maize Defense Promoting Fungal Pathogen Resistance.
Yezhang Ding,Alisa Huffaker,Tobias G. Köllner,Philipp R. Weckwerth,Christelle A. M. Robert,Joseph L. Spencer,Alexander E. Lipka,Eric A. Schmelz +7 more
TL;DR: In vivo disease resistance assays, using ZmTps21 and Zmtps21 near-isogenic lines, further support the endogenous antifungal role of selinene-derived metabolites and unexpectedly high levels of the sesquiterpene volatile β-selinene and the corresponding nonvolatile antibiotic derivative β-costic acid.
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Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values
T. Granleese,T. Granleese,Sam Clark,Andrew Swan,Julius H. J. van der Werf,Julius H. J. van der Werf +5 more
TL;DR: Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited.
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A Function Accounting for Training Set Size and Marker Density to Model the Average Accuracy of Genomic Prediction
TL;DR: The aim of this study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically.
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Genome-Wide Association Study for Spot Blotch Resistance in Hard Winter Wheat
Girma Ayana,Shaukat Ali,Jagdeep Singh Sidhu,Jose L. Gonzalez Hernandez,Brent Turnipseed,Sunish K. Sehgal +5 more
TL;DR: This study not only validates three (2D, 5A, and 7B) genomic regions identified in previous studies but also provides highly associated SNP markers for marker assisted selection.
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.