• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.913-921
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• 2019

Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.99-117
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• 2016

Data on primal cuts were collected from 1,829 steers of Hanwoo progeny testing programs, between 2010 and 2015 for the ssGWAS. SNP data were analyzed by using Illumina Bovine 50K Beadchip. The SNP data that matches with phenotype data was 674 animals. As a first step, the genomic estimated breeding value(GEBV) of the loin and rib cuts were estimated, which was used in the estimation of SNP marker effects and their variances related to the traits. Then, the estimated variance explained by each marker was expressed as a proportion to the total genetic variance. Finally, the SNP loci and their significance to any possible QTL were examined. Among the 20 best SNP loci explaining a larger proportion of SNP variance to the total genetic variance for tender loin yield, the region between 12,812,193 ~ 12,922,313bp on BTA 10 harbored a cluster of SNPs that explained about 7.32 to 7.34% of the total genetic variance. For strip loin yield, a peak for higher effects for multiple SNPs was found in BTA24, between 38,158,543 and 38,347,278bp distances, which explained about 8.36 to 8.56% of the observed variance for this trait. For loin yield had relatively smaller effects in terms of the total genetic variance. Therefore, loin yield might be affected by a few loci with moderate effects and many other loci with smaller effects across the genome.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.12
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• pp.1852-1862
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• 2018

Objective: The purpose of this study was to investigate a single step genome-wide association study (ssGWAS) for identifying genomic regions affecting reproductive traits in Landrace and Large White pigs. Methods: The traits included the number of pigs weaned per sow per year (PWSY), the number of litters per sow per year (LSY), pigs weaned per litters (PWL), born alive per litters (BAL), non-productive day (NPD) and wean to conception interval per litters (W2CL). A total of 321 animals (140 Landrace and 181 Large White pigs) were genotyped with the Illumina Porcine SNP 60k BeadChip, containing 61,177 single nucleotide polymorphisms (SNPs), while multiple traits single-step genomic BLUP method was used to calculate variances of 5 SNP windows for 11,048 Landrace and 13,985 Large White data records. Results: The outcome of ssGWAS on the reproductive traits identified twenty-five and twenty-two SNPs associated with reproductive traits in Landrace and Large White, respectively. Three known genes were identified to be candidate genes in Landrace pigs including retinol binding protein 7, and ubiquitination factor E4B genes for PWL, BAL, W2CL, and PWSY and one gene, solute carrier organic anion transporter family member 6A1, for LSY and NPD. Meanwhile, five genes were identified to be candidate genes in Large White, two of which, aldehyde dehydrogenase 1 family member A3 and leucine rich repeat kinase 1, associated with all of six reproduction traits and three genes; retrotransposon Gag like 4, transient receptor potential cation channel subfamily C member 5, and LHFPL tetraspan subfamily member 1 for five traits except W2CL. Conclusion: The genomic regions identified in this study provided a start-up point for marker assisted selection and estimating genomic breeding values for improving reproductive traits in commercial pig populations.

• Journal of Animal Science and Technology
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• v.63 no.1
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• pp.25-35
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• 2021

The purpose of this study is to estimate the single nucleotide polymorphism (SNP) effect for pH values affecting Berkshire meat quality. A total of 39,603 SNPs from 1,978 heads after quality control and 882 pH values were used estimate SNP effect by single step genomic best linear unbiased prediction (ssGBLUP) method. The average physical distance between adjacent SNP pairs was 61.7kbp and the number and proportion of SNPs whose minor allele frequency was below 10% were 9,573 and 24.2%, respectively. The average of observed heterozygosity and polymorphic information content was 0.32 ± 0.16 and 0.26 ± 0.11, respectively and the estimate for average linkage disequilibrium was 0.40. The heritability of pH45m and pH24h were 0.10 and 0.15 respectively. SNPs with an absolute value more than 4 standard deviations from the mean were selected as threshold markers, among the selected SNPs, protein-coding genes of pH45m and pH24h were detected in 6 and 4 SNPs, respectively. The distribution of coding genes were detected at pH45m and were detected at pH24h.

• Animal Bioscience
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• v.37 no.3
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• pp.451-460
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• 2024

Objective: The objective is to identify genomic regions and candidate genes associated with age to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) in Yorkshire pig. Methods: This study used a total of 104,380 records and 11,854 single nucleotide polymorphism (SNP) data obtained from Illumina porcine 60K chip. The estimated genomic breeding values (GEBVs) and SNP effects were estimated by single-step genomic best linear unbiased prediction (ssGBLUP). Results: The heritabilities of AGE, ADG, BF, and EMA were 0.50, 0.49, 0.49, and 0.23, respectively. We identified significant SNP markers surpassing the Bonferroni correction threshold (1.68×10^-6), with a total of 9 markers associated with both AGE and ADG, and 4 markers associated with BF and EMA. Genome-wide association study (GWAS) analyses revealed notable chromosomal regions linked to AGE and ADG on Sus scrofa chromosome (SSC) 1, 6, 8, and 16; BF on SSC 2, 5, and 8; and EMA on SSC 1. Additionally, we observed strong linkage disequilibrium on SSC 1. Finally, we performed enrichment analyses using gene ontology and Kyoto encyclopedia of genes and genomes (KEGG), which revealed significant enrichments in eight biological processes, one cellular component, one molecular function, and one KEGG pathway. Conclusion: The identified SNP markers for productive traits are expected to provide valuable information for genetic improvement as an understanding of their expression.

• Korean Journal of Agricultural Science
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• v.40 no.2
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• pp.155-162
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• 2013

Genome-wide association study was performed on data from 266 Hanwoo steers derived from 66 sire using bovine 10K mapping chip in Hanwoo (Korean Cattle). SNPs were excluded from the analysis if they failed in over 5% of the genotypes, had median GC scores below 0.6, had GC scores under 0.6 in less than 90% of the samples, deviated in heterozygosity more than 3 standard deviations from the other SNPs and were out of Hardy-Weinberg equilibrium for a cutoff p-value of $1^{-15}$. Unmapped and SNPs on sex chromosomes were also excluded. A total of 4,522 SNPs were included in the analysis. To test an association between SNP and QTL, GWAS for five genetic mode (additive, dominant, overdominant, recessive and codominant) was implemented in this study. Three SNPs (rs29018694, ss46526851 and rs29018222) at a threshold p< $1.11{\times}10^{-5}$ were detected on BTA12 and BTA21 for dressing percentages in codominant and recessive genetic mode. The G allele for rs29018694 has 4.9% higher dressing percentage than A allele, while the T allele for ss46526851 has 2.57 % higher dressing percentage than C allele. Therefore, rs29018694 SNP showed a bigger effect than the other two SNPs (ss46526851 and rs29018222) in this study. In conclusion, this study identifies three loci with moderate effects and many loci with infinitesimally small effect across genome in Hanwoo.