### INTRODUCTION

### MATERIALS AND METHODS

### Single nucleotide polymorphism data and quality control

^{−6}) of Hardy Weinberg disequilibrium chi square value, and genomic information of animals with more than 20% of SNP missing rate were excluded. A total of 1,038 animals passed quality control and a total of 36,392 SNP markers were used in this experiment (Table 1).

### Phenotypic data for validation of selection accuracy

### Statistical models

*y*

*= observed value of total number of piglets born, overall average,*

_{ijkl}*P*

*=*

_{i}*i*th fixed effect of parity,

*YS*

*=*

_{j}*j*th fixed effect of farrowing year-season,

*a*

*=*

_{k}*k*th additive genetic effect (breeding value),

*pe*

*=*

_{k}*k*th permanent environmental effect of animals,

*e*

*= residual effects.*

_{ijkl}#### Genetic parameters

*h*

*) and repeatability (r) calculation formulars were as follows:*

^{2}#### Estimation of genomic breeding values

*y*= n×1 vector of observation,

*b*= p×1 vector of fixed effect,

*a*=

*q*×1 vector of additive genetic random effect,

*p*=

*q*×1 vector of permanent environmental random effect, X(n×p), Z(n×q), and W(n×q) known incidence matrix corresponding to b, a, and p, e = n×1 vector of residual effect.

*A*

^{−1}= inverse matrix of numerator relationship matrix,

*G*

^{−1}= inverse matrix of genomic relationship matrix,

*r*

^{2}) of breeding value was calculated using Prediction error variance (PEV) value by the following formular.

### RESULTS AND DISCUSSION

### Genetic parameters

### Accuracy of estimated breeding value and genomic estimated breeding value

*r*

^{2}= 0.68).

### Relationship between selection ratio and phenotype

### Genetic gain

*r*

*×*

_{GP}*i*×

*σ*

_{a}*/L*, selection of sows from the tested sows for the total number of piglets born was based on pedigree information. Of 5,000 tested sows, 550 were selected (recently replacement rate of sows is 100%). Of 500 tested boars, 45 were selected. Therefore, the selection intensity (

*i*) was 1.76. Genetic standard deviation (

*σ*

*) for the total number of piglets born was 0.91. Since there was no data on the total number of piglets born for candidate pigs, the accuracy of the breeding value estimated from pedigree information was 0.080. When genomic information was used, the accuracy was 0.216 (Table 7). Assuming the replacement rate of sows per year at 100% and generation interval of 1 year, genetic gain per year would be 0.346 heads when genomic information was used and 0.128 when BLUP was used. Therefore, genetic gain estimated using ssBLUP method was 2.7 times higher than that estimated using BLUP method, i.e., 270% more efficient in improvement efficiency.*

_{a}