• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.120-120
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• 2020

Based on the simple sequence repeat (SSR) marker, a Korean wheat core collection were established with 616 wheat accessions. Among them, the SNP genotyping for the entire genome was performed using DNA chip array to clarify the whole genome SNP profiles. Consequently, a total of 35,143 SNPs were found and we re-established a mini-core collection with 247 accessions. Population diversity and phylogenetic analysis revealed genetic diversity and relationships from the mini core set. In addition, genome-wide association study (GWAS) was performed on 19 phenotypic traits; ear type, awn length, culm length, ear length, awn color, seed coat color, culm color, ear color, loading, leaf length, leaf width, seeding stand, cold damage, weight, auricle, plant type, heading stage, maturation period, upright habit, and degree of flag leaf. The GWAS was performed using the fixed and random model circulating probability unification (FarmCPU), which identified 14 to 258 SNP loci related to 19 phenotypic traits. Our study indicates that this Korean wheat mini-core collection is a set of germplasm useful for basic and applied research with the aim of understanding and exploiting the genetic diversity of Korean wheat varieties.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.4
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• pp.462-469
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• 2017

Objective: The aim of this study is to identify genomic regions or genes controlling growth traits in pigs. Methods: Using a panel of 54,148 single nucleotide polymorphisms (SNPs), we performed a genome-wide Association (GWA) study in 562 pure Yorshire pigs with four growth traits: average daily gain from 30 kg to 100 kg or 115 kg, and days to 100 kg or 115 kg. Fixed and random model Circulating Probability Unification method was used to identify the associations between 54,148 SNPs and these four traits. SNP annotations were performed through the Sus scrofa data set from Ensembl. Bioinformatics analysis, including gene ontology analysis, pathway analysis and network analysis, was used to identify the candidate genes. Results: We detected 6 significant and 12 suggestive SNPs, and identified 9 candidate genes in close proximity to them (suppressor of glucose by autophagy [SOGA1], R-Spondin 2 [RSPO2], mitogen activated protein kinase kinase 6 [MAP2K6], phospholipase C beta 1 [PLCB1], rho GTPASE activating protein 24 [ARHGAP24], cytoplasmic polyadenylation element binding protein 4 [CPEB4], GLI family zinc finger 2 [GLI2], neuronal tyrosine-phosphorylated phosphoinositide-3-kinase adaptor 2 [NYAP2], and zinc finger protein multitype 2 [ZFPM2]). Gene ontology analysis and literature mining indicated that the candidate genes are involved in bone, muscle, fat, and lung development. Pathway analysis revealed that PLCB1 and MAP2K6 participate in the gonadotropin signaling pathway and suggests that these two genes contribute to growth at the onset of puberty. Conclusion: Our results provide new clues for understanding the genetic mechanisms underlying growth traits, and may help improve these traits in future breeding programs.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

• Animal Bioscience
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• v.37 no.3
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• pp.428-436
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• 2024

Objective: This study compared five distinct sets of biological pathways and associated genes related to semen volume (VOL), number of sperm (NS), and sperm motility (MOT) in the Thai multibreed dairy population. Methods: The phenotypic data included 13,533 VOL records, 12,773 NS records, and 12,660 MOT records from 131 bulls. The genotypic data consisted of 76,519 imputed and actual single nucleotide polymorphisms (SNPs) from 72 animals. The SNP additive genetic variances for VOL, NS, and MOT were estimated for SNP windows of one SNP (SW1), ten SNP (SW10), 30 SNP (SW30), 50 SNP (SW50), and 100 SNP (SW100) using a single-step genomic best linear unbiased prediction approach. The fixed effects in the model were contemporary group, ejaculate order, bull age, ambient temperature, and heterosis. The random effects accounted for animal additive genetic effects, permanent environment effects, and residual. The SNPs explaining at least 0.001% of the additive genetic variance in SW1, 0.01% in SW10, 0.03% in SW30, 0.05% in SW50, and 0.1% in SW100 were selected for gene identification through the NCBI database. The pathway analysis utilized genes associated with the identified SNP windows. Results: Comparison of overlapping and non-overlapping SNP windows revealed notable differences among the identified pathways and genes associated with the studied traits. Overlapping windows consistently yielded a larger number of shared biological pathways and genes than non-overlapping windows. In particular, overlapping SW30 and SW50 identified the largest number of shared pathways and genes in the Thai multibreed dairy population. Conclusion: This study yielded valuable insights into the genetic architecture of VOL, NS, and MOT. It also highlighted the importance of assessing overlapping and non-overlapping SNP windows of various sizes for their effectiveness to identify shared pathways and genes influencing multiple traits.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.11
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• pp.1537-1544
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• 2015

Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l'Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.

• Genomics & Informatics
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• v.12 no.4
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• pp.254-260
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• 2014

Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-called single-nucleotide polymorphism [SNP]-BLUP), and SNP-SNP variance-covariance matrix (so-called SNP-GBLUP). We used 35,675 SNPs and R package "rrBLUP" for the BLUP analysis. The SNP-SNP relationship matrix was calculated using the GRM and Sherman-Morrison-Woodbury lemma. The SNP-GBLUP result was very similar to G-BLUP in the prediction of genetic values. However, there were many discrepancies between SNP-BLUP and the other two BLUPs. SNP-GBLUP has the merit to be able to predict genetic values through SNP effects.

• Journal of Animal Science and Technology
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• v.54 no.1
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• pp.1-8
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• 2012

This study aimed to investigate the single nucleotide polymorphisms (SNPs) of the porcine MC4R gene and validate the effect of the MC4R genotype for marker assisted selection (MAS). Six amplicons were produced to analyze the entire base sequences of the porcine MC4R gene and six SNPs were detected (c.-780C>G, c.-135C>T, c.175C>T-Leu59Leu, c.707A>G-Arg236His, c.892A>G-Asp298Asn, and c.*430A>T). Linkage disequilibrium (LD) of the six SNPs was analyzed by performing haploid analysis. There was a perfect linkage disequilibrium in c.-780C>G, c.-135C>T, c.175C>T-Leu59Leu, c.707A>G-Arg236His, and c.*430A>T. Only the c.892A>G (Asp298Asn) SNP showed a very low LD with an $r^2$ value of 0.028 and the D' value of 0.348. As a result, the two SNPs-c.707A>G (Arg236His) and c.892A>G (Asp298Asn)-were selected to extract the genotype frequencies from the 5 pig breeds by using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) genotype analysis method. The SNP frequency of c.707A>G (Arg236His) indicated the presence of the A (His) allele only in Yorkshire, while the G allele was fixed in the KNP, Landrace, Berkshire, and Duroc. Association analysis was carried out in 484 pigs with the c.707A>G (Arg236His) SNP and the meat quality traits of four different pig cross populations: a significant association was noted in crude fat, sirloin moisture, meat color, and the degree of red and yellow coloration. The frequency of the c.892A>G(Asp298Asn) SNP genotype varied among the breeds; while Duroc showed the highest frequency of the A (Asn) allele, KNP showed the highest frequency of the G (Asp) allele. Association analysis was carried out in 1126 pigs with the c.892A>G (Asp298Asn) SNP and the meat quality traits of four pig populations: a highly significant linkage was noted in the back-fat thickness (P<0.002). It was found that the back-fat thickness was higher in individuals with the AA genotype than in those with the AG or GG genotype. Thus, in this study, we verified that the c.892A>G (Asp298Asn) SNP in the pig MC4R gene has a sufficient effect as a gene marker for MAS in Korean pork industry.

• Animal Bioscience
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• v.34 no.8
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• pp.1283-1289
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• 2021

Objective: The progestogen-associated endometrial protein (PAEP) gene encodes the main whey protein in milk, β-lactoglobulin. The aim of the study was to investigate polymorphism in the PAEP gene and its association with milk yield, composition, and quality. Methods: Test-day records for 782 dairy cows were analysed. A total of 10 single nucleotide polymorphisms (SNP) within the PAEP gene were investigated. The following parameters were recorded: milk yield (MY, kg/d), percent milk fat (%), protein (PP, %), dry matter (DMP, %) and lactose (LP, %), urea content (UC, mg/L) as well as natural logarithm for somatic cell count (LnSCC, ln). Effect on genomic estimated breeding values accuracy was evaluated with pedigree and single step model. Results: Results show that only three SNPs were polymorphic, creating 5 composite genotypes: P1 to P5. Differences in MY between composite genotypes were noted in the two tested herds. Cows with P5 composite genotypes were characterised by the highest PP and LnSCC and the lowest LP and UC (p<0.05). P4 was linked to an increased DMP and UC, while P3 to an increase in LP and decrease in PP and LnSCC. Both factors are important markers in herd management and have high influences on the herds economics. For 5 out of 7 traits the accuracy of prediction was improved by including the haplotype as a fixed effect. Conclusion: Presented results may suggest a new way to optimise breeding programmes and demonstrate the impact of using genomic data during that process.

• Journal of Animal Science and Technology
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• v.65 no.5
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• pp.912-921
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• 2023

Genetic diversity analysis is crucial for maintaining and managing genetic resources. Several studies have examined the genetic diversity of Korean domestic chicken (KDC) populations using microsatellite markers, but it is difficult to capture the characteristics of the whole genome in this manner. Hence, this study analyzed the genetic diversity of several KDC populations using high-density single nucleotide polymorphism (SNP) genotype data. We examined 935 birds from 21 KDC populations, including indigenous and adapted Korean native chicken (KNC), Hyunin and Jeju KDC, and Hanhyup commercial KDC populations. A total of 212,420 SNPs of 21 KDC populations were used for calculating genetic distances and fixation index, and for ADMIXTURE analysis. As a result of the analysis, the indigenous KNC groups were genetically closer and more fixed than the other groups. Furthermore, Hyunin and Jeju KDC were similar to the indigenous KNC. In comparison, adapted KNC and Hanhyup KDC populations derived from the same original species were genetically close to each other, but had different genetic structures from the others. In conclusion, this study suggests that continuous evaluation and management are required to prevent a loss of genetic diversity in each group. Basic genetic information is provided that can be used to improve breeds quickly by utilizing the various characteristics of native chickens.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.3
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• pp.327-334
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• 2018

Objective: The objective of the present study was to validate genes and genomic regions associated with carcass weight using a low-density single nucleotide polymorphism (SNP) Chip in Hanwoo cattle breed. Methods: Commercial Hanwoo steers (n = 220) were genotyped with 20K GeneSeek genomic profiler BeadChip. After applying the quality control of criteria of a call rate ${\geq}90%$ and minor allele frequency (MAF) ${\geq}0.01$, a total of 15,235 autosomal SNPs were left for genome-wide association (GWA) analysis. The GWA tests were performed using single-locus mixed linear model. Age at slaughter was fitted as fixed effect and sire included as a covariate. The level of genome-wide significance was set at $3.28{\times}10^{-6}$ (0.05/15,235), corresponding to Bonferroni correction for 15,235 multiple independent tests. Results: By employing EMMAX approach which is based on a mixed linear model and accounts for population stratification and relatedness, we identified 17 and 16 loci significantly (p<0.001) associated with carcass weight for the additive and dominant models, respectively. The second most significant (p = 0.000049) SNP (ARS-BFGL-NGS-28234) on bovine chromosome 4 (BTA4) at 21 Mb had an allele substitution effect of 43.45 kg. Some of the identified regions on BTA2, 6, 14, 22, and 24 were previously reported to be associated with quantitative trait loci for carcass weight in several beef cattle breeds. Conclusion: This is the first genome-wide association study using SNP chips on commercial Hanwoo steers, and some of the loci newly identified in this study may help to better DNA markers that determine increased beef production in commercial Hanwoo cattle. Further studies using a larger sample size will allow confirmation of the candidates identified in this study.