• Asian-Australasian Journal of Animal Sciences
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• v.22 no.1
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• pp.124-130
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• 2009

Estimating genetic interaction effects in animal genomics would be one of the most challenging studies because the phenotypic variation for economically important traits might be largely explained by interaction effects among multiple nucleotide sequence variants under various environmental exposures. Genetic improvement of economic animals would be expected by understanding multi-locus genetic interaction effects associated with economic traits. Most analyses in animal breeding and genetics, however, have excluded the possibility of genetic interaction effects in their analytical models. This review discusses a historical estimation of the genetic interaction and difficulties in analyzing the interaction effects. Furthermore, two recently developed methods for assessing genetic interactions are introduced to animal genomics. One is the restricted partition method, as a nonparametric grouping-based approach, that iteratively utilizes grouping of genotypes with the smallest difference into a new group, and the other is the Bayesian method that draws inferences about the genetic interaction effects based on their marginal posterior distributions and attains the marginalization of the joint posterior distribution through Gibbs sampling as a Markov chain Monte Carlo. Further developing appropriate and efficient methods for assessing genetic interactions would be urgent to achieve accurate understanding of genetic architecture for complex traits of economic animals.

• Journal of agriculture & life science
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• v.51 no.6
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• pp.89-105
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• 2017

This study utilized 32,312 records of 17 linear type and 10 conformation traits(including final scores) of Hanwoo cows in the KAIA(Korea Animal Improvement Association) ('09~'10), with 60,556 animals in the pedigree file. Traits included stature, body length, strength, body depth, angularity, shank thickness, rump angle, rump length, pin bone width, thigh thickness, udder volume, teat length, teat placement, foot angle, hock angle, rear leg back view, body balance, breed characteristic, head development, forequarter quality, back line, rump, thigh development, udder development, leg line, and final score. Genetic and residual(co) variances were estimated using bi-trait pairwise analyses with EM-REML algorithm. Herd-year-classifier, year at classification, and calving stage were considered as fixed effects with classification months as a covariate. The heritability estimates ranged from 0.03(teat placement) to 0.42(body length). Rump length had the highest positive genetic correlation with pin bone width(0.96). Moreover, stature, body length, strength, and body depth had the highest positive genetic correlations with rump length, pin bone width, and thigh thickness(0.81-0.94). Stature, body length, strength, body depth, rump length, pin bone width, and thigh thickness traits also had high positive genetic correlations.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.245-251
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• 2015

Records of 490,767 cows collected from 1990 to 2012 by dairy herd milk test of National Agriculture Cooperative Federation The pedigree of dairy cattle were provided by Korea Animal Improvement Association. The data were used to analyze the longevity of dairy cows with the life traits such as days in milk, number of lactation, productive life, and life span. The data were also used to investigate genetic relationship of these longevity traits with profitability of dairy cows, including heritability and genetic correlation. The profitability was calculated with simulation of milk income and production costs for individual cows. Days in milk among the traits had -0.287, -0.572 and -0.536 of genetic correlation with number of lactations, productive life and lifespan, respectively. The heritabilities of life span, number of lactations, productive life, and days in milk were found to be 0.045, 0.047, 0.059 and 0.081, respectively. Genetic correlations of profit with productive life, number of lactations, and days in milk were identified as 0.072, 0.080, 0.098 and 0.101. These results suggested that days in milk was most desirable traits to represent longevity of Holstein dairy cattle. In general, since longevity and profitability were close genetic relationship each other, genetic improvement of longevity is necessary for better profitable cows.

• Korean Journal of Plant Resources
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• v.24 no.3
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• pp.272-279
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• 2011

It is very crucial to evaluate the genetic diversity of peanut genetic resources for identification of peanut germplasm accessions and variety improvement. Cultivated peanut generally has two subspecies, hypogaea and fastigiata. In this study, we identified peanut into three plant types, virginia (var. hypogaea), spanish (var. vulgaris), and valencia (var. fastigiata). Former one belongs to ssp. hypogaea and latter two are involved in ssp. fastigiata. Twenty SSR markers were used to assess the genetic variation of three sets, hypogaea, vulgaris, and fastigiata, respectively. Out of variety-specific SSR primers tried in this study, ten pairs of SSR primers showed polymorphisms. Each accession could be identified by a specific set of polymorphic SSR primers, and allele number was evaluated among accessions, with an average of 6.7 in var. hypogaea and 5.4 in var. vulgaris and fastigiata. For evaluation of genetic diversity, gene diversity ranged from 0.336 to 0.844 and PIC (polymorphism information contents) ranged from 0.324 to 0.827 were investigated. Dendrograms based on genetic distances were constructed, which showed the existence of three different clusters. And these three different clusters might be associated with the genes involved in three plant types. The results also suggested that there were plentiful SSR polymorphisms among peanut germplasm accessions in RDA (Rural Development Administration, Korea) Genebank and SSRs might play an important role in evaluating peanut accessions and cultivar improvement.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.4
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• pp.525-530
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• 2020

Objective: The purpose of this study was i) to identify the characteristics of carcass traits in Chikso by gender, region, age at slaughter, and coat color using the carcass data collected from the nationwide pedigree information and coat color investigation, and ii) to estimate genetic parameters for breed improvement. Methods: A linear model was used to analyze the environmental effects on the carcass traits and to estimate genetic parameters. Analysis of variance was performed using TYPE III sum of squares for the unbalanced data provided by the general linear model procedure. Variance components for genetic parameters was estimated using REMLF90 of the BLUPF90 family programs. Results: Phenotypic performance of carcass weight (CW), eye muscle area (EMA), and backfat thickness (BF) in Chikso were lower than those of Hanwoo. This is a natural outcome because Hanwoo have undergone significant efforts for improvement at the national level, a phenomenon not observed in Chikso. Another factor influencing the above outcome was the smaller population size of Chikso compared to that of Hanwoo's. The heritabilities of CW, EMA, BF, and marbling score in Chikso were estimated as 0.50, 0.37, 0.35, and 0.53, respectively, which were was higher than those of Hanwoo. Conclusion: Based on the genetic parameters that were estimated in this study, it is expected that the carcass traits will improve when the livestock research institutes at each province conduct small-scale performance tests and the semen is provided to farmers after selecting proven bulls using the state-of-art selection technique such as genomic selection.

• Korean Journal of Plant Resources
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• v.17 no.3
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• pp.265-271
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• 2004

Genetic variation is the basis of crop improvement. Limited genetic diversity in a crop species may restrict the amount of genetic improvement that can be achieved through plant breeding. Soybean is one of the world's most important crops. A potential source of genetic variability for the cultivated soybean is the wild species G. soja Sieb. ＆amp; Zucc. Amplified fragment length polymorphism (AFLP) analysis is a PCR-based technique, which can detect a 10-fold greater nubmer of loci than other DNA marker analysis. Twenty cultivated soybeans and two-hundred wild soybeans were used to determine genetic vatiations by AFLPs and evaluate the usefulness of AFLPs as DNA markers. Six-hundred and ten fragments were detected with an average of 56 AFLP fragments produced per primer in a total of 11 AFLP primer pairs. The number of polymorphic loci detected per primer ranged from 7 to 20 and the polymorphism was greater in wild than in cultivated soybean. F$_2$ segregation analysis of four AFLP fragments in combination of Hwaeomputkong ${\times}$ PI 417479 indicated that they segregate as stable Mendelian loci with 3 : 1. This results strongly suggest that the AFLP analysis is a good technique for the detection of genetic polymorphism in a wide plant species.

• Animal Bioscience
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• v.34 no.8
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• pp.1303-1308
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• 2021

Objective: The objective of this study was to define a new composite trait for Holstein dairy cows and evaluate the possibility of joint improvement in milk and fertility traits. Methods: A data set consisting 35,882 fertility related records (days open [DO], calving interval [CI], and number of services per conception [NSC], and total milk yield in each lactation [TMY]) was collected from 1998 to 2016 in Polish Holstein-Friesian breed herds. In this study TMY, DO, CI, and lactation length of each cow was used to obtain composite milk and fertility traits (CMF). Results: Moderate heritability (0.15) was estimated for composite trait that was higher than heritability of female fertility related traits: DO 0.047, CI 0.042, and NSC 0.014, and slightly lower than heritability of TMY 0.19. Favourable genetic correlations (-0.87) were estimated between CMF with TMY. Spearman rank correlation coefficients between breeding value of CMF with DO, CI, and TMY were high (>0.94) but with NSC were moderate (0.64). Selection on CMF caused favourable correlated genetic gains for DO, CI, and TMY. Different selection indices with different emphasis on fertility and milk production were constructed. The amount of correlated genetic gains obtained for DO and total milk production according to selection in CMF were higher than of genetic gains obtained for DO and TMY in selection indices with different emphasis on milk and fertility. Conclusion: The animal selection only based on a composite trait - CMF proposed in current study would simultaneously lead to favourable genetic gains for both milk and fertility related traits. In this situation CMF introduced in current study can be used to overcome to limitations of selection index and CMF could be useful for countries that have problems in recording traits, especially functional traits.

• IE interfaces
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• v.15 no.3
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• pp.241-246
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• 2002

Some extensions of minimum spanning tree problem are NP-hard problem in which polynomial-time solutions for them do not exist. Because of their complexity, recently some researcher have used the genetic algorithms to solve them. In genetic algorithm approach the Prufer number is usually used to represent a tree. In this paper we discuss the problem of the Prufer number encoding method and propose an improved genetic operation. Using a numerical comparison we demonstrate the excellence of the proposed method.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.2
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• pp.197-202
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• 2020

Objective: The objective of this study was to identify environmental factors strongly associated with and to estimate genetic parameters of reproductive traits in Japanese Black heifers. Methods: Data included reproduction records of Japanese Black heifers born between 2004 and 2014. First service non-return rate (NRR) to 56 days from first to successful insemination (FS), number of services per conception (IN), age at first calving (AFC) and gestation length were analyzed with the use of the general linear model. Genetic parameters were estimated with the use of the univariate animal model of the residual maximum likelihood. Results: Averages of reproductive traits over eleven years were assessed, and the effects of farm, year, month, artificial insemination technician and interaction of farm×year on the traits were determined. Estimated heritability of FS was very low and that of AFC was higher than that of the other traits. A close genetic relation was observed among NRR, IN, and FS; however, their heritabilities were very low. AFC shows favorable genetic correlation with IN and FS. Conclusion: Low heritabilities of most reproductive traits in Japanese Black heifers are strongly influenced by farm management practices, and that large residual variances make genetic evaluation difficult. Among the reproductive traits, AFC is potentially more useful for genetic improvement of heifer reproductive traits because it has high heritability and favorable genetic correlations with IN and FS.

• Journal of Sasang Constitutional Medicine
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• v.32 no.2
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• pp.10-21
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• 2020

Objectives Genome-wide association studies(GWAS) is a useful method to identify genetic associations for various phenotypes. The purpose of this study was to develop predictive models for Sasang constitution types using genetic factors. Methods The genotypes of the 1,999 subjects was performed using Axiom Precision Medicine Research Array (PMRA) by Life Technologies. All participants were prescribed Sasang Constitution-specific herbal remedies for the treatment, and showed improvement of original symptoms as confirmed by Korean medicine doctor. The genotypes were imputed by using the IMPUTE program. Association analysis was conducted using a logistic regression model to discover Single Nucleotide Polymorphism (SNP), adjusting for age, sex, and BMI. Results & Conclusions We developed models to predict Korean medicine constitution types using identified genectic factors and sex, age, BMI using Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN). Each maximum Area Under the Curve (AUC) of Teaeum, Soeum, Soyang is 0.894, 0.868, 0.767, respectively. Each AUC of the models increased by 6~17% more than that of models except for genetic factors. By developing the predictive models, we confirmed usefulness of genetic factors related with types. It demonstrates a mechanism for more accurate prediction through genetic factors related with type.