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Genomic selection using low density marker panels with application to a sire line in pigs

BACKGROUND: Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide p...

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Autores principales: Wellmann, Robin, Preuß, Siegfried, Tholen, Ernst, Heinkel, Jörg, Wimmers, Klaus, Bennewitz, Jörn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750593/
https://www.ncbi.nlm.nih.gov/pubmed/23895218
http://dx.doi.org/10.1186/1297-9686-45-28
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author Wellmann, Robin
Preuß, Siegfried
Tholen, Ernst
Heinkel, Jörg
Wimmers, Klaus
Bennewitz, Jörn
author_facet Wellmann, Robin
Preuß, Siegfried
Tholen, Ernst
Heinkel, Jörg
Wimmers, Klaus
Bennewitz, Jörn
author_sort Wellmann, Robin
collection PubMed
description BACKGROUND: Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip. RESULTS: Genotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density. Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown. CONCLUSIONS: Genomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound.
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spelling pubmed-37505932013-08-27 Genomic selection using low density marker panels with application to a sire line in pigs Wellmann, Robin Preuß, Siegfried Tholen, Ernst Heinkel, Jörg Wimmers, Klaus Bennewitz, Jörn Genet Sel Evol Research BACKGROUND: Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip. RESULTS: Genotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density. Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown. CONCLUSIONS: Genomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound. BioMed Central 2013-07-29 /pmc/articles/PMC3750593/ /pubmed/23895218 http://dx.doi.org/10.1186/1297-9686-45-28 Text en Copyright © 2013 Wellmann et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Wellmann, Robin
Preuß, Siegfried
Tholen, Ernst
Heinkel, Jörg
Wimmers, Klaus
Bennewitz, Jörn
Genomic selection using low density marker panels with application to a sire line in pigs
title Genomic selection using low density marker panels with application to a sire line in pigs
title_full Genomic selection using low density marker panels with application to a sire line in pigs
title_fullStr Genomic selection using low density marker panels with application to a sire line in pigs
title_full_unstemmed Genomic selection using low density marker panels with application to a sire line in pigs
title_short Genomic selection using low density marker panels with application to a sire line in pigs
title_sort genomic selection using low density marker panels with application to a sire line in pigs
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750593/
https://www.ncbi.nlm.nih.gov/pubmed/23895218
http://dx.doi.org/10.1186/1297-9686-45-28
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