• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1066-1073
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• 2017

Objective: Growth-related traits are important economic traits in the swine industry. However, the genetic mechanism of growth-related traits is little known. The aim of this study was to screen the candidate genes and molecular markers associated with body dimension and body weight traits in pigs. Methods: A genome-wide association study (GWAS) on body dimension and body weight traits was performed in a White $Duroc{\times}Erhualian$ $F_2$ intercross by the illumina PorcineSNP60K Beadchip. A mixed linear model was used to assess the association between single nucleotide polymorphisms (SNPs) and the phenotypes. Results: In total, 611 and 79 SNPs were identified significantly associated with body dimension traits and body weight respectively. All SNPs but 62 were located into 23 genomic regions (quantitative trait loci, QTLs) on 14 autosomal and X chromosomes in Sus scrofa Build 10.2 assembly. Out of the 23 QTLs with the suggestive significance level ($5{\times}10^{-4}$), three QTLs exceeded the genome-wide significance threshold ($1.15{\times}10^{-6}$). Except the one on Sus scrofa chromosome (SSC) 7 which was reported previously all the QTLs are novel. In addition, we identified 5 promising candidate genes, including cell division cycle 7 for abdominal circumference, pleiomorphic adenoma gene 1 and neuropeptides B/W receptor 1 for both body weight and cannon bone circumference on SSC4, phosphoenolpyruvate carboxykinase 1, and bone morphogenetic protein 7 for hip circumference on SSC17. Conclusion: The results have not only demonstrated a number of potential genes/loci associated with the growth-related traits in pigs, but also laid a foundation for studying the genes' role and further identifying causative variants underlying these loci.

• Genomics & Informatics
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• v.10 no.2
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• pp.117-122
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• 2012

A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.309-319
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• 2017

Objective: Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods: This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results: We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion: This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.9
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• pp.1234-1240
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• 2009

Gene flow, genetic structure and differentiation of Kutchi, Mehsana and Sirohi breeds of goat from North-Western India were evaluated based on 25 microsatellite markers so as to support breed conservation and improvement decisions. The microsatellite genotyping was carried out using an automated DNA sequencer. The gene diversity across the studied loci for the Kutchi breed varied from 0.57 (ILST 065) to 0.93 (OarFCB 304, OMHC 1, ILSTS 058) with an overall mean of 0.79${\pm}$0.02. The corresponding values for Mehsana and Sirohi breeds were 0.16 (ILST 008) to 0.93 (OMHC 1, ILSTS 058) with an average of 0.76${\pm}$0.04, and 0.50 (ILSTS 029) to 0.94 (ILSTS 058) with an average of 0.78${\pm}$0.02, respectively. The Mehsana breed had lowest gene diversity among the 3 breeds studied. All the populations showed an overall significant heterozygote deficit ($F_{is}$). The Fis values were 0.26, 0.14 and 0.36 for Kutchi, Mehsana and Sirohi goat breeds, respectively. Kutchi and Mehsana were more differentiated (16%) followed by Mehsana and Sirohi (13%).The measures of standard genetic distance between pairs of breeds indicated that the lowest genetic distance was between Kutchi and Sirohi breeds (0.73) and the largest genetic distance was between Mehsana and Kutchi (1.0) followed by Sirohi and Mehsana (0.75) breeds. Mehsana and Kutchi are distinct breeds and this was revealed by the estimated genetic distance between them. All measures of genetic variation revealed substantial genetic variation in each of the populations studied, thereby showing good scope for their further improvement.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.6
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• pp.763-770
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• 2015

Improved meat quality and greater muscle yield are highly sought after in high-quality chicken breeding programs. Past studies indicated that polymorphisms of the Perilipin gene (PLIN1) are highly associated with adiposity in mammals and are potential molecular markers for improving meat quality and carcass traits in chickens. In the present study, we screened single nucleotide polymorphisms (SNPs) in all exons of the PLIN1 gene with a direct sequencing method in six populations with different genetic backgrounds (total 240 individuals). We evaluated the association between the polymorphisms and carcass and meat quality traits. We identified three SNPs, located on the 5' flanking region and exon 1 of PLIN1 on chromosome 10 (rs315831750, rs313726543, and rs80724063, respectively). Eight main haplotypes were constructed based on these SNPs. We calculated the allelic and genotypic frequencies, and genetic diversity parameters of the three SNPs. The polymorphism information content (PIC) ranged from 0.2768 to 0.3750, which reflected an intermediate genetic diversity for all chickens. The CC, CT, and TT genotypes influenced the percentage of breast muscle (PBM), percentage of leg muscle (PLM) and percentage of abdominal fat at rs315831750 (p<0.05). Diplotypes (haplotype pairs) affected the percentage of eviscerated weight (PEW) and PBM (p<0.05). Compared with chickens carrying other diplotypes, H3H7 had the greatest PEW and H2H2 had the greatest PBM, and those with diplotype H7H7 had the smallest PEW and PBM. We conclude that PLIN1 gene polymorphisms may affect broiler carcass and breast muscle yields, and diplotypes H3H7 and H2H2 could be positive molecular markers to enhance PEW and PBM in chickens.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• Journal of Korean Neurosurgical Society
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• v.64 no.2
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• pp.309-315
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• 2021

Objective : To explore the correlation between the polymorphism of histone deacetylase 9 gene (rs1060499865, rs723296, rs957960) and ischemic stroke (IS) in Chinese Han population in Dali region. Methods : This study included 155 IS patients and 128 healthy physical examinees. TaqMan-polymerase chain reaction technology and multivariate logistic regression were performed. Results : In the case group, there was no polymorphism of rs1060499865 observed in the two groups; whereas on the rs723296 locus the frequencies of C allele and TC genotype were significantly higher than that in the control group, alleles C and T were associated with a 2.158-fold increase in IS risk, and genotypes TC and TT were associated with a 2.269-fold increase in IS risk. The locus rs957960 exhibited no significant difference between the two groups. Conclusion : An association between rs723296 and the risk of IS was found in the Chinese Han population in Dali region. No significant association was found between rs1060499865, rs957960 and IS in the Chinese Han population in Dali region.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.8
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• pp.1071-1078
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• 2006

Three buffalo populations viz. Bhadawari, Tarai and local buffaloes of Kerala were genotyped using 24 heterologous polymorphic microsatellite loci. A total of 140 alleles were observed with an average observed heterozygosity of 0.63. All the loci were neutral and 18 out of the 24 loci were in Hardy Weinberg Equilibrium. The $F_{IS}$ values (estimate of inbreeding) for 16 loci in all the three populations were negative. This indicated lack of population structure in the three populations. The effective number of immigrants was 5.88 per generation between the Tarai and Bhadawari populations which was quite high suggesting substantial gene flow. The genetic distances revealed closeness between the Tarai and Bhadawari populations which was expected from geographical contiguity. The FST values were not significantly different from zero showing no population differentiation. The Correspondence Analysis based on the allelic frequency data clustered the majority of the Tarai and Bhadawari individuals as an admixture.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.5
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• pp.510-513
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• 1997

This study examined the effects of ignoring inbreeding depression on (co)variance components for weaning weight through the use of Monte Carlo simulation. Weaning weight is of particular interest as a trait for which additive direct and maternal genetic components exist and there then is the potential for a direct-maternal genetic covariance. Ignoring inbreeding depression in the analytical model (.8 kg reduction of phenotypic value per 1% inbreeding) led to biased estimates of all genetic (co) variance components, all estimates being larger than the true values of the parameters. In particular, a negative bias in the direct-maternal genetic covariance was observed in analyses that ignored inbreeding depression. A small spurious sire-by-year interaction variance was also observed.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.10
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• pp.1399-1405
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• 2014

The effective management of endangered animal genetic resources is one of the most important concerns of modern breeding. Evaluation of genetic diversity and relationship of local breeds is an important factor towards the identification of unique and valuable genetic resources. This study aimed to analyze the genetic diversity and population structure of six Korean native chicken breeds (n = 300), which were compared with three imported breeds in Korea (n = 150). For the analysis of genetic diversity, 30 microsatellite markers from FAO/ISAG recommended diversity panel or previously reported microsatellite markers were used. The number of alleles ranged from 2 to 15 per locus, with a mean of 8.13. The average observed heterozygosity within native breeds varied between 0.46 and 0.59. The overall heterozygote deficiency ($F_{IT}$) in native chicken was $0.234{\pm}0.025$. Over 30.7% of $F_{IT}$ was contributed by within-population deficiency ($F_{IS}$). Bayesian clustering analysis, using the STRUCTURE software suggested 9 clusters. This study may provide the background for future studies to identify the genetic uniqueness of the Korean native chicken breeds.