Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle

<p>Abstract</p> <p>Background</p> <p>Low cost genotyping of individuals using high density genomic markers were recently introduced as genomic selection in genetic improvement programs in dairy cattle. Most implementations of genomic selection only use marker informatio...

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Main Authors: Jensen Just, Su Guosheng, Madsen Per
Format: Article
Language:English
Published: BMC 2012-06-01
Series:BMC Genetics
Subjects:
Online Access:http://www.biomedcentral.com/1471-2156/13/44
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spelling doaj-2ed083db9c29429f90c6252fabea1c802020-11-25T03:38:41ZengBMCBMC Genetics1471-21562012-06-011314410.1186/1471-2156-13-44Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattleJensen JustSu GuoshengMadsen Per<p>Abstract</p> <p>Background</p> <p>Low cost genotyping of individuals using high density genomic markers were recently introduced as genomic selection in genetic improvement programs in dairy cattle. Most implementations of genomic selection only use marker information, in the models used for prediction of genetic merit. However, in other species it has been shown that only a fraction of the total genetic variance can be explained by markers. Using 5217 bulls in the Nordic Holstein population that were genotyped and had genetic evaluations based on progeny, we partitioned the total additive genetic variance into a genomic component explained by markers and a remaining component explained by familial relationships. The traits analyzed were production and fitness related traits in dairy cattle. Furthermore, we estimated the genomic variance that can be attributed to individual chromosomes and we illustrate methods that can predict the amount of additive genetic variance that can be explained by sets of markers with different density.</p> <p>Results</p> <p>The amount of additive genetic variance that can be explained by markers was estimated by an analysis of the matrix of genomic relationships. For the traits in the analysis, most of the additive genetic variance can be explained by 44 K informative SNP markers. The same amount of variance can be attributed to individual chromosomes but surprisingly the relation between chromosomal variance and chromosome length was weak. In models including both genomic (marker) and familial (pedigree) effects most (on average 77.2%) of total additive genetic variance was explained by genomic effects while the remaining was explained by familial relationships.</p> <p>Conclusions</p> <p>Most of the additive genetic variance for the traits in the Nordic Holstein population can be explained using 44 K informative SNP markers. By analyzing the genomic relationship matrix it is possible to predict the amount of additive genetic variance that can be explained by a reduced (or increased) set of markers. For the population analyzed the improvement of genomic prediction by increasing marker density beyond 44 K is limited.</p> http://www.biomedcentral.com/1471-2156/13/44Genomic variancePolygenic varianceChromosomesComplex traitsDairy cattle genetic markers
collection DOAJ
language English
format Article
sources DOAJ
author Jensen Just
Su Guosheng
Madsen Per
spellingShingle Jensen Just
Su Guosheng
Madsen Per
Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
BMC Genetics
Genomic variance
Polygenic variance
Chromosomes
Complex traits
Dairy cattle genetic markers
author_facet Jensen Just
Su Guosheng
Madsen Per
author_sort Jensen Just
title Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
title_short Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
title_full Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
title_fullStr Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
title_full_unstemmed Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
title_sort partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle
publisher BMC
series BMC Genetics
issn 1471-2156
publishDate 2012-06-01
description <p>Abstract</p> <p>Background</p> <p>Low cost genotyping of individuals using high density genomic markers were recently introduced as genomic selection in genetic improvement programs in dairy cattle. Most implementations of genomic selection only use marker information, in the models used for prediction of genetic merit. However, in other species it has been shown that only a fraction of the total genetic variance can be explained by markers. Using 5217 bulls in the Nordic Holstein population that were genotyped and had genetic evaluations based on progeny, we partitioned the total additive genetic variance into a genomic component explained by markers and a remaining component explained by familial relationships. The traits analyzed were production and fitness related traits in dairy cattle. Furthermore, we estimated the genomic variance that can be attributed to individual chromosomes and we illustrate methods that can predict the amount of additive genetic variance that can be explained by sets of markers with different density.</p> <p>Results</p> <p>The amount of additive genetic variance that can be explained by markers was estimated by an analysis of the matrix of genomic relationships. For the traits in the analysis, most of the additive genetic variance can be explained by 44 K informative SNP markers. The same amount of variance can be attributed to individual chromosomes but surprisingly the relation between chromosomal variance and chromosome length was weak. In models including both genomic (marker) and familial (pedigree) effects most (on average 77.2%) of total additive genetic variance was explained by genomic effects while the remaining was explained by familial relationships.</p> <p>Conclusions</p> <p>Most of the additive genetic variance for the traits in the Nordic Holstein population can be explained using 44 K informative SNP markers. By analyzing the genomic relationship matrix it is possible to predict the amount of additive genetic variance that can be explained by a reduced (or increased) set of markers. For the population analyzed the improvement of genomic prediction by increasing marker density beyond 44 K is limited.</p>
topic Genomic variance
Polygenic variance
Chromosomes
Complex traits
Dairy cattle genetic markers
url http://www.biomedcentral.com/1471-2156/13/44
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AT suguosheng partitioningadditivegeneticvarianceintogenomicandremainingpolygeniccomponentsforcomplextraitsindairycattle
AT madsenper partitioningadditivegeneticvarianceintogenomicandremainingpolygeniccomponentsforcomplextraitsindairycattle
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