• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1077-1083
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• 2019

Objective: Sow longevity is important for efficient and profitable pig farming. Recently, there has been an increasing interest in social genetic effect (SGE) of pigs on stress-tolerance and behavior. The present study aimed to estimate genetic correlations among average daily gain (ADG), stayability (STAY), and number of piglets born alive at the first parity (NBA1) in Korean Yorkshire pigs, using a model including SGE. Methods: The phenotypic records of ADG and reproductive traits of 33,120 and 11,654 pigs, respectively, were evaluated. The variances and (co) variances of the studied traits were estimated by a multi-trait animal model applying the Bayesian with linear-threshold models using Gibbs sampling. Results: The direct and SGEs on ADG had a significantly negative (-0.30) and neutral (0.04) genetic relationship with STAY, respectively. In addition, the genetic correlation between the social effects on ADG and NBA1 tended to be positive (0.27), unlike the direct effects (-0.04). The genetic correlation of the total effect on ADG with that of STAY was negative (-0.23) but non-significant, owing to the social effect. Conclusion: These results suggested that total genetic effect on growth in the SGE model might reduce the negative effect on sow longevity because of the growth potential of pigs. We recommend including social effects as selection criteria in breeding programs to obtain satisfactory genetic changes in both growth and longevity.

• 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.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.595-602
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• 2016

In pigs, individuals in the same pen may show aggressive behavior toward each other, such as tail biting. Such social interactions among pen mates may considerably affect their welfare and performance, both in negative and positive ways. The present study was conducted to investigate social genetic effects on days to 90 kg using data from 12,208 Duroc and Yorkshire pigs that were born between 2008 and 2012. Heritability was estimated using the five following animal models: a basic model with direct heritable effects only (Model 1), a social model with direct and social heritable effects (Model 2), a model accounting for covariance between direct and social heritable effects (Model 3), and two models considering a dilution factor with direct and social heritable effects (Models 4 and 5). The optimal model to represent Duroc pigs was Model 1 which only uses direct heritable effects. Direct heritability (0.21) was higher than total heritability (0.09) and covariance was negative. Model 2 was evaluated as the optimum model for Yorkshire pigs. Yorkshire data showed that total heritability (0.5) was twice as high as direct heritability (0.25) and covariance was positive. Our results suggest that the efficiency of social effects differed among breeding lines. Further research on social effects related to breeds by group size would clarify which is the most efficient selection method that accounts for social genetic effects.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.493-504
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• 2011

The present paper presents a genetic algorithm (GA) to maximize social welfare and perform congestion management by optimally placing and sizing one Thyristor-Controlled Series Capacitor (TCSC) device in a double-sided auction market. Simulation results, with line flow constraints before and after the compensation, are compared through the Sequential Quadratic Programming SQP method, and are used to analyze the effect of TCSC on the congestion levels of modified IEEE 14-bus and 30-bus test systems. Quadratic, smooth and nonsmooth (with sine components due to valve point loading effect) generator cost curves, and quadratic smooth consumer benefit functions are considered. The main aims of the present study are the inclusion of customer benefit in the social welfare maximization and congestion management objective function, the consideration of nonsmooth generator characteristics, and the optimal locating and sizing of the TCSC using real code-based GA to guarantee fast convergence to the best solution.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.563-573
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• 2012

Various methods of analysis have been proposed to understand the gene-disease relation and gene-gene interaction effect for a disease through comparison of genotype in case-control study. In this study, we proposed the method to detect a genetic association and gene-gene interaction through the use of a network graph and centrality measures that are used in social network analysis. The applicability of the proposed method was studied through an analysis of real genetic data.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1836-1843
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• 2019

Objective: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ${\omega}$ constants for genomic relationships. Methods: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (${\tau}:1$), several weights (${\omega}_{xx}$, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). Results: The genetic variances and total heritability estimates ($T^2$) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ${\omega}$ other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ${\omega}$ in both breeds, indicating the better accuracy of ${\omega}_{0.1}$ models. Therefore, the optimal values of ${\omega}$ to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. Conclusion: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.323-335
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• 2016

Breast cancer risk assessment has developed during years and evaluation of genetic factor affecting risk of breast cancer is an important component of this risk assessment. The aim of this meta-analysis was to investigate the role of XRCC1 polymorphisms (Arg194Trp, Arg280His and Arg399Gln) in risk of breast cancer among different population and categories of menopausal status.PubMed, Medline, Web of Science, and PubMed Central were systematically searched to identify studies evaluating association between breast cancer and XRCC1 gene polymorphisms (Arg194Trp, Arg280His and Arg399Gln). Two authors independently extracted required information. Odds Ratios were pooled for four genetic inheritance models using both fixed and the DerSimonian and Laird random-effect models. Egger's test and contour-enhanced funnel plot was used to evaluate publication bias and small study effect. Additional subgroup analysis was performed for menopausal status, ethnicity, and source of controls. After evaluation and applying inclusion criteria on extracted studies, fifty three studies were included in this meta-analysis. For polymorphisms of Arg194Trp and Arg280His, no significant association was observed in all genetic models. Arg194Trp had a protective effect in post-menopausal status only in homozygote model (OR=0.57 [0.37-0.88]). Arg399Gln showed significant association with breast cancer in homozygote (OR=1.21 [1.10-1.34]), dominant (OR=1.09 [1.03-1.15]) and recessive (OR=1.21 [1.09- 1.35]) genetic models. Arg399Gln was associated with higher risk in post-menopausal status for homozygote and heterozygote models. Our findings suggest that XRCC1 gene polymorphisms modify breast cancer risk in different populations and different categories of menopausal status.

• Journal of Plant Biotechnology
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• v.40 no.4
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• pp.185-191
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• 2013

Over the past decades, carbon dioxide concentration of the atmosphere of the world has increased significantly, and thereby the greenhouse effect has become a social issue. To solve this problem, new renewable energy sources including solar, hydrogen, geothermal, wind and bio-energy are suggested as alternatives. Among these new energy sources, bio-energy crops are widely introduced and under rapid progress. For example, corn and oilseed rape plants are used for the production of bio-ethanol and bio-diesel, respectively. However, grain prices has increased severely because of the use of corn for bio-ethanol production. Therefore, non-edible switchgrass draws attention as an alternative source for bio-ethanol production in USA. This review describes the shortage of fossil energy and an importance of switchgrass as a bio-energy crop. Also, some characteristics of its major cultivars are introduced including growth habit, total output of biomass yields. Furthermore, biotechnological approaches have been conducted to improve the productivity of switchgrass using tissue culture and genetic transformation.

• Anxiety and mood
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• v.16 no.2
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• pp.57-75
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• 2020

Particular matter is steadily increasing due to environmental factors at domestic and abroad such as industry and economy. Recently, the exposure particular matters has been reported to increase the risk not only for morbidity and mortality, but also for diseases of the respiratory system, cardiovascular system and central nervous system/neuropsychiatric disorder. Although the causes of neuropsychiatric diseases are genetic and environmental factors, it is necessary to pay more attention to environmental factors in terms of prevention. We mainly describe environmental factors that affect neuropsychiatric disorders, mainly on particular matter, which is one of harmful environmental substances. In the current study, we reviewed evidence for the presence of particular matter or particular matter related harmful air pollutants-O₃, SO₂, NO₂/NOx, traffic related air pollution, that may represent risk factors for the development of neuropsychiatric disorder.

• The Plant Pathology Journal
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• v.39 no.1
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• pp.39-51
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• 2023

Common bean (Phaseolus vulgaris L.) is one of the most important crops in human food production. The occurrence of diseases, such as white mold, caused by Sclerotinia sclerotiorum can limit the production of this legume. The use of Trichoderma has become an important strategy in the suppression of this disease. The aim of the present study was to evaluate the effect of volatile organic compounds (VOCs) emitted by Trichoderma azevedoi CEN1241 in five different growth periods on the severity of white mold in common bean. The in vitro assays were carried out in double-plate and split-plate, and the in vivo assays, through the exposure of the mycelia of S. sclerotiorum to the VOCs of T. azevedoi CEN1241 and subsequent inoculation in bean plants. Chemical analysis by gas chromatography coupled to mass spectrometry detected 37 VOCs produced by T. azevedoi CEN1241, covering six major chemical classes. The profile of VOCs produced by T. azevedoi CEN1241 varied according to colony age and was shown to be related to the ability of the biocontrol agent to suppress S. sclerotiorum. T. azevedoi CEN1241 VOCs reduced the size of S. sclerotiorum lesions on bean fragments in vitro and reduced disease severity in a greenhouse. This study demonstrated in a more applied way that the mechanism of antibiosis through the production of volatile compounds exerted by Trichoderma can complement other mechanisms, such as parasitism and competition, thus contributing to a better efficiency in the control of white mold in bean plants.