• Asian-Australasian Journal of Animal Sciences
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• v.31 no.6
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• pp.784-790
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• 2018

Objective: The genetic effects of an individual on the phenotypes of its social partners, such as its pen mates, are known as social genetic effects. This study aims to identify the candidate genes for social (pen-mates') average daily gain (ADG) in pigs by using the genome-wide association approach. Methods: Social ADG (sADG) was the average ADG of unrelated pen-mates (strangers). We used the phenotype data (16,802 records) after correcting for batch (week), sex, pen, number of strangers (1 to 7 pigs) in the pen, full-sib rate (0% to 80%) within pen, and age at the end of the test. A total of 1,041 pigs from Landrace breeds were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel, which comprised 61,565 single nucleotide polymorphism (SNP) markers. After quality control, 909 individuals and 39,837 markers remained for sADG in genome-wide association study. Results: We detected five new SNPs, all on chromosome 6, which have not been associated with social ADG or other growth traits to date. One SNP was inside the prostaglandin $F2{\alpha}$ receptor (PTGFR) gene, another SNP was located 22 kb upstream of gene interferon-induced protein 44 (IFI44), and the last three SNPs were between 161 kb and 191 kb upstream of the EGF latrophilin and seven transmembrane domain-containing protein 1 (ELTD1) gene. PTGFR, IFI44, and ELTD1 were never associated with social interaction and social genetic effects in any of the previous studies. Conclusion: The identification of several genomic regions, and candidate genes associated with social genetic effects reported here, could contribute to a better understanding of the genetic basis of interaction traits for ADG. In conclusion, we suggest that the PTGFR, IFI44, and ELTD1 may be used as a molecular marker for sADG, although their functional effect was not defined yet. Thus, it will be of interest to execute association studies in those genes.

• Genomics & Informatics
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• v.14 no.2
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• pp.62-68
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• 2016

Osteoporosis is a medical condition of global concern, with increasing incidence in both sexes. Bone mineral density (BMD), a highly heritable trait, has been proven a useful diagnostic factor in predicting fracture. Because medical information is lacking about male osteoporotic genetics, we conducted a genome-wide association study of BMD in Korean men. With 1,176 participants, we analyzed 4,414,664 single nucleotide polymorphisms (SNPs) after genomic imputation, and identified five SNPs and three loci correlated with bone density and strength. Multivariate linear regression models were applied to adjust for age and body mass index interference. Rs17124500 ($p=6.42{\times}10^{-7}$), rs34594869 ($p=6.53{\times}10^{-7}$) and rs17124504 ($p=6.53{\times}10^{-7}$) in 14q31.3 and rs140155614 ($p=8.64{\times}10^{-7}$) in 15q25.1 were significantly associated with lumbar spine BMD (LS-BMD), while rs111822233 ($p=6.35{\times}10^{-7}$) was linked with the femur total BMD (FT-BMD). Additionally, we analyzed the relationship between BMD and five genes previously identified in Korean men. Rs61382873 (p = 0.0009) in LRP5, rs9567003 (p = 0.0033) in TNFSF11 and rs9935828 (p = 0.0248) in FOXL1 were observed for LS-BMD. Furthermore, rs33997547 (p = 0.0057) in ZBTB and rs1664496 (p = 0.0012) in MEF2C were found to influence FT-BMD and rs61769193 (p = 0.0114) in ZBTB to influence femur neck BMD. We identified five SNPs and three genomic regions, associated with BMD. The significance of our results lies in the discovery of new loci, while also affirming a previously significant locus, as potential osteoporotic factors in the Korean male population.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.735-747
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• 2023

The composition of fatty acids determines the flavor and quality of meat. Flavor compounds are generated during the cooking process by the decomposition of volatile fatty acids via lipid oxidation. A number of research on candidate genes related to fatty acid content in livestock species have been published. The majority of these studies focused on pigs and cattle; the association between fatty acid composition and meat quality in chickens has rarely been reported. Therefore, this study investigated candidate genes associated with fatty acid composition in chickens. A genome-wide association study (GWAS) was performed on 767 individuals from an F2 crossbred population of Yeonsan Ogye and White Leghorn chickens. The Illumina chicken 60K significant single-nucleotide polymorphism (SNP) genotype data and 30 fatty acids (%) in the breast meat of animals slaughtered at 10 weeks of age were analyzed. SNPs were shown to be significant in 15 traits: C10:0, C14:0, C18:0, C18:1n-7, C18:1n-9, C18:2n-6, C20:0, C20:2, C20:3n-6, C20:4n-6, C20:5n-3, C24:0, C24:1n-9, monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA). These SNPs were mostly located on chromosome 10 and around the following genes: ACSS3, BTG1, MCEE, PPARGC1A, ACSL4, ELOVL4, CYB5R4, ME1, and TRPM1. Both oleic acid and arachidonic acid contained the candidate genes: MCEE and TRPM1. These two fatty acids are antagonistic to each other and have been identified as traits that contribute to the production of volatile fatty acids. The results of this study improve our understanding of the genetic mechanisms through which fatty acids in chicken affect the meat flavor.

• Interdisciplinary Bio Central
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• v.6 no.1
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• pp.1.1-1.6
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• 2014

A growing body of evidence shows that most psychological traits are polygenic, that is they involve the action of many genes with small effects. However, the study of selection has disproportionately been on one or a few genes and their associated sweep signals (rapid and large changes in frequency). If our goal is to study the evolution of psychological variables, such as intelligence, we need a model that explains the evolution of phenotypes governed by many common genetic variants. This study illustrates simple statistical tools to detect signals of recent polygenic selection: a) ANOVA can be used to reveal significant deviation from random distribution of allele frequencies across racial groups. b) Principal component analysis can be used as a tool for finding a factor that represents the strength of recent selection on a phenotype and the underlying genetic variation. c) Method of correlated vectors: the correlation between genetic frequencies and the average phenotypes of different populations is computed; then, the resulting correlation coefficients are correlated with the corresponding alleles' genome-wide significance. This provides a measure of how selection acted on genes with higher signal to noise ratio. Another related test is that alleles with large frequency differences between populations should have a higher genome-wide significance value than alleles with small frequency differences. This paper fruitfully employs these tools and shows that common genetic variants exhibit subtle frequency shifts and that these shifts predict phenotypic differences across populations.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.1
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• pp.28-32
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• 2012

In the present study, we evaluated the informativeness of SNPs genotyped by the Illumina Bovine SNP50K assay in different cattle breeds. To investigate these on a genome-wide scale, we considered 52,678 SNPs spanning the whole autosomal and X chromosomes in cattle. Our study samples consists of six different cattle breeds. Across the breeds approximately 72 and 6% SNPs were found polymorphic and fixed or close to fix in all the breeds, respectively. The variations in the average minor allele frequency (MAF) were significantly different between the breeds studied. The level of average MAF observed in Hanwoo was significantly lower than the other breeds. Hanwoo breed also displayed the lowest number of polymorphic SNPs across all the chromosomes. More importantly, this study indicated that the Bovine SNP50K assay will have reduced power for genome-wide association studies in Hanwoo as compared to other cattle breeds. Overall, the Bovine SNP50K assay described in this study offer a useful genotyping platform for mapping quantitative trait loci (QTLs) in the cattle breeds. The assay data represent a vast and generally untapped resource to assist the investigation of the complex production traits and the development of marker-assisted selection programs.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.54 no.3
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• pp.332-338
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• 2009

Rapid extension of genomic database leads to the remarkable advance of functional genomics. This study proposes a novel methodology of functional analysis using 5-methyltrytophan (5 MT) mutant together with their 2-DE analysis and public microarray database. A total of 24 proteins was changed in 5 MT mutant and four remarkably different expressed proteins were identified. Among them, three spots were converted to Affymetrix probe. A total of 155 microarray samples from Gene Expression Omnibus (GEO) in NCBI was retrieved and followed by constructing gene co-expression networks over a broad range of biological issues through Self-Organising Tree Algorithm. Three co-expressing gene clusters were retrieved and each functional categorization with differential expression pattern was exhibited from 5 MT resistance mutant rice. It was indicated new co-expression networks in the mutant. This study suggests that on investigating possibility which correspond 2-DE to microarray database with their full potential.

• Korean Journal of Veterinary Service
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• v.42 no.4
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• pp.217-225
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• 2019

To detect Single nucleotide polymorphisms (SNP) markers associated with Bovine viral diarrhea virus (BVDV) and Bovine respiratory syncytial virus (BRSV) S/P ratio in Korean Holstein dairy cattle, Genome-wide association study (GWAS) was performed using Illumina BovineSNP50 Beadchip. The number of phenotype data and genotype data were 107, and 294. respectively. Phenotype data were collected for four periods (0 week, 1 week, 4 week, 24 week) after having vaccinated (0 week no vaccinated period). A total of 36,257 SNPs was remained after quality control had been done by PLINK. The result of GWAS showed 6 SNP markers (BTB-01704243, BTB-01594395, ARS-BFGL-NGS-118070, ARS-BFGL-NGS-111365, BTA-65410-no-rs, Hapmap38331-BTA-61256) under BVDV and 4 SNP markers (ARS-BFGL-NGS-109861, Hapmap53701-rs29017064, ARS-BFGL-NGS-71055, BTA-11232-no-rs) under BRSV. And also, 10 candidate genes found through 10 SNP markers (TBX18, CEP162, PAFAH1B1, METTL16, BRCA1, RND2, POLK, ENSBTAG00000051724, ADAM18, NRG3).

• BMB Reports
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• v.41 no.8
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• pp.609-614
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• 2008

The concentrations and catalytic activities of enzymes control metabolic rates. Previous studies have focused on enzyme concentrations because there are no genome-wide techniques used for the measurement of enzyme activity. We propose a method for evaluating the significance of enzyme activity by integrating metabolic network topologies and genome-wide microarray gene expression profiles. We quantified the enzymatic activity of reactions and report the 388 significant reactions in five perturbation datasets. For the 388 enzymatic reactions, we identified 70 that were significantly regulated (P-value < 0.001). Thirty-one of these reactions were part of anaerobic metabolism, 23 were part of low-pH aerobic metabolism, 8 were part of high-pH anaerobic metabolism, 3 were part of low-pH aerobic reactions, and 5 were part of high-pH anaerobic metabolism.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.356-359
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• 2009

In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating geneenvironment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.

• Journal of Genetic Medicine
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• v.17 no.1
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• pp.1-10
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• 2020

Polycystic ovarian syndrome (PCOS) is the most common endocrine disorder in women, which is characterized by the oligo/anovulation, hyperandrogenism (HA) and polycystic ovarian morphology which are diagnostic criteria. PCOS has diverse clinical aspects in addition to those diagnostic criteria including increased risk for cardiovascular diseases, metabolic syndrome, dyslipidemia, type 2 diabetes and impaired fertility. Because of the heterogeneity of the disease, the pathogenesis of the disease has not been elucidated yet. Therefore, there is no cure for the endocrinopathy. HA and insulin resistance (IR) has been considered two major pillars of the pathogenesis of PCOS. Recent advances in animal studies revealed the critical role of neuroendocrine abnormalities in developing PCOS. Several pathways related to neuroendocrine origin have been investigated such as hypothalamus pituitary ovarian axis, hypothalamus pituitary adrenal axis and hypothalamus pituitary adipose axis. This review summarizes the current knowledge about the role of HA and IR in developing PCOS. In addition, we review the results of recent genome wide association studies for PCOS. This new perspective improves our understanding of the role of neuroendocrine origins in PCOS and suggest a novel potential therapeutic target for the treatment of PCOS.