• 가정과삶의질연구
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• 제19권6호
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• pp.221-239
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• 2001

The purpose of this research was to identify arid to compare stereotypes toward the elderly held by adolescents and middle-aged adults. Stereotypes toward the elderly were examined at two levels: to assess students′and middle-aged adults′beliefs about the traits of the elderly and to categorize the traits into stereotypes. Traits groupings were analyzed with hierarchical cluster analysis. The main results of this study were as follows: First, both adolescents and middle-aged adults believed the negative stereotypes were more characteristic of the elderly than the positive ones. Second, middle-aged adults reported more complex negative stereotype sets of the elderly than adolescents. Third, Adolescents reported even more negative physical appearance trails of elderly persons than the middle-aged. Fourth, the traits endorsed as characteristics of elderly persons were often contradictory within two age groups. For example, adolescents perceived "sacrifice" as a positive trait of the elderly, while middle-aged adults perceived it as a negative one.

• 한국양식학회지
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• 제18권2호
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• pp.130-132
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• 2005

Genomics research has two ultimate applied goals: to Isolate and clone genes of economic importance for bio-technology and gene-assisted selection (GAS), and to locate and use markers for marker-assisted selection (MAS) in selective breeding programs. To this end, we have identified linked markers for feed conversion efficiency growth rate, and disease resistance to enteric septicemia of catfish (ESC). Three microsatellite markers Ip266, Ip384, and Ip607 were identified to be linked to feed conversion efficiency. Similarly one marker each was identified to be linked to growth rate (Ip607) and disease resistance to ESC (Ip477). Ip607 marker linked to both growth rate and feed conversion efficiency, indicating that the QTL for both growth rate and feed conversion efficiency may either be the same or located in the same chromosomal region in the catfish genome. On phenotypic evaluation, certain traits such as growth rate can be accurately evaluated by body weight evaluation while other traits such as disease resistance can be quite complex. The linked DNA markers will be highly useful for MAS programs and for directing further efforts of genomic mapping for important quantitative traits.

• Reproductive and Developmental Biology
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• 제37권4호
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• pp.185-192
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• 2013

Many countries have implemented genetic evaluation for fertility traits in recent years. In particular, reproductive trait is a complex trait and need to require a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with reproductive trait, we applied a weighted gene co-expression network analysis from expression value of bovine genes. We identified three co-expressed modules associated with reproductive trait from bovine microarray data. Hub genes (ZP4, FHL2 and EGR4) were determined in each module; they were topologically centered with statistically significant value in the gene co-expression network. We were able to find the highly co-expressed gene pairs with a correlation coefficient. Finally, the crucial functions of co-expressed modules were reported from functional enrichment analysis. We suggest that the network-based approach in livestock may an important method for analyzing the complex effects of candidate genes associated with economic traits like reproduction.

• Animal Bioscience
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• 제34권6호
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• pp.967-974
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• 2021

Objective: The objective of this study was to estimate the genetic correlation (rpc) of growth performance between purebred (Duroc and Korean native) and synthetic (WooriHeukDon) pigs using a single-step method. Methods: Phenotypes of 15,902 pigs with genotyped data from 1,792 pigs from a nucleus farm were used for this study. We estimated the rpc of several performance traits between WooriHeukDon and purebred pigs: day of target weight (DAY), backfat thickness (BF), feed conversion rate (FCR), and residual feed intake (RFI). The variances and covariances of the studied traits were estimated by an animal multi-trait model that applied the Bayesian inference. Results: rpc within traits was lower than 0.1 for DAY and BF, but high for FCR and RFI; in particular, rpc for RFI between Duroc and WooriHeukDon pigs was nearly 1. Comparison between different traits revealed that RFI in Duroc pigs was associated with different traits in WooriHeukDon pigs. However, the most of rpc between different traits were estimated with low or with high standard deviation. Conclusion: The results indicated that there were substantial differences in rpc of traits in the synthetic WooriHeukDon pigs, which could be caused by these pigs having a more complex origin than other crossbred pigs. RFI was strongly correlated between Duroc and WooriHeukDon pigs, and these breeds might have similar single nucleotide polymorphism effects that control RFI. RFI is more essential for metabolism than other growth traits and these metabolic characteristics in purebred pigs, such as nutrient utilization, could significantly affect those in synthetic pigs. The findings of this study can be used to elucidate the genetic architecture of crossbred pigs and help develop new breeds with target traits.

• Genomics & Informatics
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• 제2권1호
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• pp.1-6
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• 2004

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1194-1204
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• 2023

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b^*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b^*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

• 대한가정학회지
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• 제48권6호
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• pp.17-30
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• 2010

The purpose of this study was to investigate the effects of young children's temperament, emotional intelligence, social behavior and mother's personality traits, and management strategy of peer relations on peer acceptance. Subjects were 412 5-years-old children and their mothers in Busan. The children responded to the Peer Nomination Inventory to assess peer acceptance and their teachers completed the EAS(Emotionality, Activity, Sociability), to assess the emotional intelligence and social behavior of the children. Mothers completed Eysenck Personality Questionnaire for personality traits and the Parental Involvement Checklist. Data was analyzed with descriptive statistics, Pearson's correlation, and simple and multiple regression analyses. The results showed that emotional intelligence of young children had a relatively significant effect on peer acceptance, followed by personality traits of mother's extraversion, the temperament of activity, and the management strategy of mediation-supervision. In conclusion, young children and their mother's variables have a complex, rather than simple, effect on peer acceptance of the children.

• International Journal of Industrial Entomology and Biomaterials
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• 제20권2호
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• pp.37-43
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• 2010

The wild silkworm, Antheraea mylitta Drury (Lepidoptera: Saturniidae) is a polyphagous silk producing insect that feeds on Terminalia arjuna, T. tomentosa and Shorea robusta and is distributed in the forest belts in different states of India. Phenotypically distinct populations of the A. mylitta are called "eco-race" or "ecotypes". Genetic improvement of this wild silkworm has not progressed much due to lack of adequate information on the factors that control the expression of most of the economically important traits. Considering the amazing technological advances taking place in molecular biology, it is envisaged that it is now possible to take greater control on these intractable traits if a combination of genetic, molecular and bioinformatics tools are used. Linkage disequilibrium (LD) mapping is one such approach that has extensively been used in both animal and plant system to identify quantitative trait loci (QTLs) for a number of economically important traits. LD mapping has a number of advantages over conventional biparental linkage mapping. Therefore, LD mapping is considered more efficient for gene discovery to meet the challenge of connecting sequence diversity with heritable phenotypic differences. However, care must be taken to avoid detection of spurious associations which may occur due to population structure and variety interrelationships. In this review, we discuss how LD mapping is suitable for the dissection of complex traits in wild silkworms (Antheraea mylitta).

• Asian-Australasian Journal of Animal Sciences
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• 제18권8호
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• pp.1088-1097
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• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.