Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction

<p>Abstract</p> <p>Background</p> <p>The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.</p> <...

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Main Authors: Rensing Stephan, Reinhardt Friedrich, Seefried Franz R, Liu Zengting, Thaller Georg, Reents Reinhard
Format: Article
Language:deu
Published: BMC 2011-05-01
Series:Genetics Selection Evolution
Online Access:http://www.gsejournal.org/content/43/1/19
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spelling doaj-20492740c4144411a6ec25d3c71eacb62020-11-24T21:12:53ZdeuBMCGenetics Selection Evolution0999-193X1297-96862011-05-014311910.1186/1297-9686-43-19Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic predictionRensing StephanReinhardt FriedrichSeefried Franz RLiu ZengtingThaller GeorgReents Reinhard<p>Abstract</p> <p>Background</p> <p>The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.</p> <p>Methods</p> <p>Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17,429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values.</p> <p>Results</p> <p>As the number of reference bulls increased, both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population.</p> <p>Conclusions</p> <p>Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability, as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values, decreased the correlation between direct genomic values and sire's estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values.</p> http://www.gsejournal.org/content/43/1/19
collection DOAJ
language deu
format Article
sources DOAJ
author Rensing Stephan
Reinhardt Friedrich
Seefried Franz R
Liu Zengting
Thaller Georg
Reents Reinhard
spellingShingle Rensing Stephan
Reinhardt Friedrich
Seefried Franz R
Liu Zengting
Thaller Georg
Reents Reinhard
Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
Genetics Selection Evolution
author_facet Rensing Stephan
Reinhardt Friedrich
Seefried Franz R
Liu Zengting
Thaller Georg
Reents Reinhard
author_sort Rensing Stephan
title Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
title_short Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
title_full Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
title_fullStr Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
title_full_unstemmed Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
title_sort impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction
publisher BMC
series Genetics Selection Evolution
issn 0999-193X
1297-9686
publishDate 2011-05-01
description <p>Abstract</p> <p>Background</p> <p>The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information.</p> <p>Methods</p> <p>Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17,429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values.</p> <p>Results</p> <p>As the number of reference bulls increased, both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population.</p> <p>Conclusions</p> <p>Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability, as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values, decreased the correlation between direct genomic values and sire's estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values.</p>
url http://www.gsejournal.org/content/43/1/19
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