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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Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.
TL;DR: The history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas are discussed.
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The future of parentage analysis: From microsatellites to SNPs and beyond.
Sarah P. Flanagan,Adam Jones +1 more
TL;DR: It is found that single nucleotide polymorphisms (SNPs), the typical next‐generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP‐based parentage analyses published thus far.
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Epidemiology and Heritability of Major Depressive Disorder, Stratified by Age of Onset, Sex, and Illness Course in Generation Scotland: Scottish Family Health Study (GS:SFHS).
Ana Maria Fernandez-Pujals,Mark Adams,Pippa A. Thomson,Andrew McKechanie,Douglas Blackwood,Blair H. Smith,Anna F. Dominiczak,Andrew D. Morris,Keith Matthews,Archie Campbell,Pamela Linksted,Chris Haley,Ian J. Deary,David J. Porteous,Donald J. MacIntyre,Andrew M. McIntosh +15 more
TL;DR: This study found an intriguing difference in heritability between recurrent and single MDD illness course, which confirms a moderate genetic contribution to depression, with a small contribution of the common family environment and supports the relationship of MDD with previously identified risk factors.
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Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle
Mehrnush Forutan,Mehrnush Forutan,Saeid Ansari Mahyari,Christine F. Baes,Nina Melzer,Flavio S Schenkel,Mehdi Sargolzaei +6 more
TL;DR: This study shows that existing software based on the measurement of ROH can accurately identify autozygosity across the genome, provided appropriate threshold parameters are used.
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Genomic inbreeding and relationships among Holsteins, Jerseys, and Brown Swiss
TL;DR: R rates of increase in genomic and pedigree inbreeding per generation should be slightly reduced with genomic selection, in agreement with previous simulations.
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.