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. 2013 Jul 29;45(1):28.
doi: 10.1186/1297-9686-45-28.

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

Affiliations

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

Robin Wellmann et al. Genet Sel Evol. .

Abstract

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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Figures

Figure 1
Figure 1
Illustration of the definition ofch,imkfor imputation of maternally inherited alleles. Haplotype i is the maternal haplotype of the individual; haplotype h is one of the haplotypes from the haplotype library that is to be scored; for a specified value of k (k = 0, 1, 2, 3, 4), the number ch,imk of markers for which there were exactly k haplotype conflicts in the interval between the respective marker allele and marker m was calculated; with respect to marker m, the number of markers with k = 0 conflict is ch,im0=6; for k = 1, 2, 3, 4, the numbers of markers with k conflicts are ch,im1=5, ch,im2=5, ch,im3=3, and ch,im4=3, respectively.
Figure 2
Figure 2
Imputation error rate for low-density panels with a) 384 markers, b) 768 markers, and c) 3000 markers plotted against chromosomal position. For each chromosome, a spline is plotted to illustrate the trend in the imputation error rate along the chromosome; error rates for markers on different chromosomes are shown in different colours; markers on the X chromosome are on the right hand side; the positions of the markers from the low-density panel are indicated by black points on the x-axis. The labels show for every panel the number of markers and the mean error rate of markers with known position.
Figure 3
Figure 3
Correlation between direct genomic values (DGV) and BLUP estimated breeding values (EBV). The regression lines show how the correlation between DGV and EBV depends on the accuracies of the EBV in the validation set; the solid line corresponds to the situation in which complete pedigrees were used for the calculation of EBV; for the dotted line, shortened pedigrees were used.

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