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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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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