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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Improved estimation of inbreeding and kinship in pigs using optimized SNP panels
Marcos S. Lopes,Fabyano Fonseca e Silva,Barbara Harlizius,N. Duijvesteijn,Paulo Sávio Lopes,Simone Ef Guimarães,Egbert F. Knol +6 more
TL;DR: Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated, however, a larger number of SNPs might be necessary in other populations or across lines.
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Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas)
Alejandro P. Gutierrez,Jane E. Symonds,Nick King,Konstanze Steiner,Tim P. Bean,Ross D. Houston +5 more
TL;DR: The potential for genomic selection for host resistance to OsHV-1 in Pacific oysters is evaluated, and it is demonstrated that a low number of SNPs might suffice to obtain accurate genomic estimated breeding values, thus potentially making the implementation of GS more cost effective.
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Identification of Mendelian inconsistencies between SNP and pedigree information of sibs
TL;DR: Tests to remove Mendelian inconsistencies between sibs should be preceded by a test for parent-offspring inconsistencies, which should not only consider parent-offspring pairs based on pedigree data, but also those based on SNP information.
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A data-driven simulation platform to predict cultivars' performances under uncertain weather conditions.
TL;DR: A computer simulation platform that uses Monte Carlo methods to integrate uncertainty about future weather conditions and model parameters is presented, and the phenotypes generated by the simulation platform have multiple downstream uses.
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Fluctuating selection on migrant adaptive sodium transporter alleles in coastal Arabidopsis thaliana.
Silvia Busoms,Pirita Paajanen,Sarah Marburger,Sian Bray,Xin-Yuan Huang,Charlotte Poschenrieder,Levi Yant,David E. Salt +7 more
TL;DR: It is demonstrated that the proportion of plants harboring HKT1;1HLS-harboring plants are better adapted to intermediate levels of salinity, and the HKT 1;1 HLS allele clusters with high-sodium accumulator accessions worldwide are a worldwide determinant in adaptation to saline conditions.
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.