• 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.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.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.7
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• pp.915-921
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• 2005

Genetic variation at 25 microsatellite loci, population structure, and genetic bottleneck hypothesis were examined for Ankleshwar poultry population found in Gujrat, India. The estimates of genetic variability such as effective number of alleles and gene diversities revealed substantial genetic variation frequently displayed by microsatellite markers. The average polymorphism across the studied loci and the expected gene diversity in the population were 6.44 and 0.670${\pm}$0.144, respectively. The population was observed to be significantly differentiated into different groups, and showed fairly high level of inbreeding (f = 0.240${\pm}$0.052) and global heterozygote deficit. The bottleneck analysis indicated the absence of genetic bottleneck in the past. The study revealed that the Ankleshwar poultry breed needs appropriate genetic management for its conservation and improvement. The information generated in this study may further be utilized for studying differentiation and relationships among different Indian poultry breeds.

• Animal Bioscience
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• v.36 no.8
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• pp.1156-1166
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• 2023

Objective: Pork belly is a cut of meat with high worldwide demand. However, although the belly is comprised of multiple muscles and fat, unlike the loin muscle, research on their genetic parameters has yet to focus on a representative cut. To use swine breeding, it is necessary to estimate heritability against pork belly traits. Moreover, estimating genetic correlations is needed to identify genetic relationship among the traditional carcass and meat quality traits. This study sought to estimate the heritability of the carcass, belly, and their component traits, as well as the genetic correlations among them, to confirm whether these traits can be improved. Methods: A total of 543 Yorkshire pigs (406 castrated males and 137 females) from 49 sires and 244 dam were used in this study. To estimate genetic parameters, a total of 12 traits such as lean meat production ability, meat quality and pork belly traits were chosen. The heritabilities were estimated by using genome-wide efficient mixed model association software. The statistical model was selected so that farm, carcass weight, sex, and slaughter season were fixed effects. In addition, its genetic parameters were calculated via MTG2 software. Results: The heritability estimates for the 7th belly slice along the whole plate and its components were low to moderate (0.07±0.07 to 0.33±0.07). Moreover, the genetic correlations among the carcass and belly traits were moderate to high (0.28±0.20 to 0.99±0.31). Particularly, the rectus abdominis muscle exhibited a high absolute genetic correlation with the belly and meat quality (0.73±52 to 0.93±0.43). Conclusion: A moderate to high correlation coefficient was obtained based on the genetic parameters. The belly could be genetically improved to contain a larger proportion of muscle regardless of lean meat production ability.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.125-134
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• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. In the genetic process of the simple GAs, there are three basic operators: reproduction, cross-over, and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying GAs to optimum design examples.

• Genomics & Informatics
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• v.8 no.3
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• pp.101-102
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• 2010

During the last decade, large community cohorts have been established by the Korea National Institutes of Health (KNIH), and enormous epidemiological and clinical data have been accumulated. Using these information and samples in the cohorts, KNIH set out to do a large-scale genome-wide association study (GWAS) in 2007, and the Korea Association REsource (KARE) consortium was launched to analyze the data to identify the underlying genetic risk factors of diseases and diverse health indexes, such as blood pressure, obesity, bone density, and blood biochemical traits. The consortium consisted of 6 research divisions, formed by 25 principal investigators in 19 organizations, including 18 universities, 2 institutes, and 1 company. Each division focused on one of the following subjects: the identification of genetic factors, the statistical analysis of gene-gene interactions, the genetic epidemiology of gene-environment interactions, copy number variation, the bioinformatics related to a GWAS, and a GWAS of nutrigenomics. In this special issue, the study results of the KARE consortium are provided as 9 articles. We hope that this special issue might encourage the genomics community to share data and scientists, including clinicians, to analyze the valuable Korean data of KARE.

• Journal of Korean Association for Spatial Structures
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• v.8 no.3
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• pp.75-82
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• 2008

In this study, the modified genetic algorithm, D-GA, is proposed. D-GA is a hybrid genetic algorithm combined a simple genetic algorithm and the local search algorithm using direction vectors. Also, two types of direction vectors, learning direction vector and random direction vector, are defined without the sensitivity analysis. The accuracy of D-GA is compared with that of simple genetic algorithm. It is demonstrated that the proposed approach can be an effective optimization technique through a minimum weight structural optimization of ten bar truss.

• Genomics & Informatics
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• v.16 no.4
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• pp.39.1-39.3
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• 2018

The rapid increase in genetic dataset volume has demanded extensive adoption of biological knowledge to reduce the computational complexity, and the biological pathway is one well-known source of such knowledge. In this regard, we have introduced a novel statistical method that enables the pathway-based association study of large-scale genetic dataset-namely, PHARAOH. However, researcher-level application of the PHARAOH method has been limited by a lack of generally used file formats and the absence of various quality control options that are essential to practical analysis. In order to overcome these limitations, we introduce our integration of the PHARAOH method into our recently developed all-in-one workbench. The proposed new PHARAOH program not only supports various de facto standard genetic data formats but also provides many quality control measures and filters based on those measures. We expect that our updated PHARAOH provides advanced accessibility of the pathway-level analysis of large-scale genetic datasets to researchers.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.733-743
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• 2010

Recently, disease-genetic association analyses using single nucleotide polymorphisms(SNPs) and haplotypes in family-based genetic study have come into the spotlight. In binary trait, the classic transmission disequilibrium test(TDT) can only be applied if genetic information of parents and their offspring is available. However, in case of diseases having a late age of onset such as dementia, the TDT cannot be applied due to the fact that parental genotype data are unavailable. For this reason, alternate methods using genetic sib information instead of parental genotype data are proposed. In this study, methods using genetic sib information are reviewed and power of analysis tests is also compared throughout simulation experiment.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.10
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• pp.1491-1500
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• 2019

Objective: European pigs have been imported to improve the economically important traits of Thai pigs by crossbreeding and was finally completely replaced. Currently Thai indigenous pigs are particularly kept in a small population. Therefore, indigenous pigs risk losing their genetic diversity and identity. Thus, this study was conducted to perform large-scale genetic diversity and phylogenetic analyses on the many pig breeds available in Thailand. Methods: Genetic diversity and phylogenetics analyses of 222 pigs belonging to Thai native pigs (TNP), Thai wild boars (TWB), European commercial pigs, commercial crossbred pigs, and Chinese indigenous pigs were investigated by genotyping using 26 microsatellite markers. Results: The results showed that Thai pig populations had a high genetic diversity with mean total and effective ($N_e$) number of alleles of 14.59 and 3.71, respectively, and expected heterozygosity ($H_e$) across loci (0.710). The polymorphic information content per locus ranged between 0.651 and 0.914 leading to an average value above all loci of 0.789, and private alleles were found in six populations. The higher $H_e$ compared to observed heterozygosity ($H_o$) in TNP, TWB, and the commercial pigs indicated some inbreeding within a population. The Nei's genetic distance, mean $F_{ST}$ estimates, neighbour-joining tree of populations and individual, as well as multidimensional analysis indicated close genetic relationship between Thai indigenous pigs and some Chinese pigs, and they are distinctly different from European pigs. Conclusion: Our study reveals a close genetic relationship between TNP and Chinese pigs. The genetic introgression from European breeds is found in some TNP populations, and signs of genetic erosion are shown. Private alleles found in this study should be taken into consideration for the breeding program. The genetic information from this study will be a benefit for both conservation and utilization of Thai pig genetic resources.