Using a very low-density SNP panel for genomic selection in a breeding program for sheep

Table 3 Genetic gain, inbreeding increase, (G)EBV accuracies, and imputation concordance rates for the GSs_Icd genomic design using VLD densities of 250, 500, and 1000 SNPs (standard deviations for 50 replicates shown in brackets)

Scenarios	GSs Icd^a	GSs Icd^a	GSs_Icd^a
Number of SNPs	1000	500	250
Genetic gain^b (σ_a/year)	0.230 (0.014)	0.183 (0.016)	0.175 (0.015)
Inbreeding^c	0.0031 (0.0006)	0.0037 (0.0007)	0.0040 (0.0010)
GEBV accuracy^d
Dams^e	0.83 (0.02)	0.74 (0.02)	0.73 (0.03)
Male candidates	0.63 (0.05)	0.45 (0.07)	0.38 (0.02)
Imputation concordance rate^f
Dams^e	96.1 (0.1)	91.8 (0.3)	87.3 (0.4)
Old females^g	93.3 (0.1)	88.7 (0.2)	84.5 (0.3)
Male candidates	96.5 (0.1)	92.4 (0.3)	88.0 (0.4)

^aGSs_Icd = genomic selection design, sires had medium-density genotypes and candidates and dams had medium-density genotypes imputed from very low-density genotypes
^bComputed as the slope of the average true breeding value of females in first parity between time10 and time25
^cComputed as the slope of the average inbreeding coefficient of females in first parity between time10 and time25
^dComputed as the average Pearson correlation between the true breeding value and (genomic) estimated breeding values of animals at time 25
^eDams mated at time 25
^fComputed as the average of number of correctly imputed SNP divided by the number of imputed SNP obtained for the imputation realized at time 25
^gDams not present anymore at time 25

ISSN: 1297-9686