• Asian-Australasian Journal of Animal Sciences
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• 제13권8호
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• pp.1035-1039
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• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• Asian-Australasian Journal of Animal Sciences
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• 제20권11호
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• pp.1631-1635
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• 2007

Japanese Brown cattle, one of the four domestic beef breeds in Japan, are suffering from numerical reduction due to economic pressure from profitable breeds. In this study, all the reproductive cows in the Kouchi sub-breed of the Japanese Brown cattle that were alive in July 2005 were investigated by pedigree analysis to clarify genetic structure and composition of genetic variability. In addition, genetically important individuals for the maintenance of genetic variability of the sub-breed were also identified through the core set method. The number of cows analyzed was 1,349. Their pedigrees were traced back to ancestors born around 1940, and pedigree records of 13,157 animals were used for the analysis. Principal component analysis was performed on the relationship matrix of the cows, and their factor loadings were plotted on a three-dimensional diagram. According to their spatial positions in the diagram, all the cows were subdivided into five genetically distinctive subpopulations of 131 to 437 animals. Genetic diversity of the whole sub-breed, which is estimated to be 0.901, was decomposed into 0.856 and 0.045 of within-subpopulation and between-subpopulation components. Recalculation of genetic diversity after removal of one or several subpopulations from the five subpopulations suggested that three of them were genetically important for the maintenance of genetic variability of the sub-breed. Applying the core set method to all the cows, maximum attainable genetic diversity was estimated to be 0.949, and optimal genetic contributions assigned to each cow supported the previous results indicating relative importance of the three subpopulations as useful genetic materials.

• 한국동물학회지
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• 제34권2호
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• pp.228-231
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• 1991

한국인 383명의 Compiement Component 6(C6)의 유전적 다형을 등전점 전기영동과 immunoblotting으로 조사하였다. 5가지 allotypes, C6 A, C6 B, C6 B2, C6 Ml, C6 M11이 나타났고, 이들의 대립유전인자 빈도는 C6*A=0.4399, C6*B=0.5144, C6*B2=0.0392로 산출되어 이는 동아시아인과 비슷하였다.

• Animal Bioscience
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• 제36권8호
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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.

• Animal Bioscience
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• 제34권4호
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• pp.471-481
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• 2021

Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

• Asian-Australasian Journal of Animal Sciences
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• 제21권8호
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• pp.1109-1115
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• 2008

The reproduction component traits are important components of sow efficiency. The objective of this study was to evaluate the phenotypic and genetic parameters of four reproduction component traits (age at puberty (AP), preweaning number dead (PND), weaning to service interval (WSI), and intra-individual SD in litter size (IISDLS)) of sows in two Chinese indigenous pig breeds. Available reproductive records including 22,591 piglets born from 2,054 litters by 574 Jiangquhai sows and 464 Meishan sows were used in this investigation. A set of mixed models and restricted maximum likelihood methodology were used for the multiple trait analyses of these traits. The results showed that the estimates of heritabilities (${\pm}$standard error) for AP, PND, WSI and IISDLS were $0.40{\pm}0.05$, $0.06{\pm}0.03$, $0.20{\pm}0.02$ and 0.09{\pm}0.03 in Jiangquhai sows, and $0.35{\pm}0.06$, $0.05{\pm}0.03$, $0.18{\pm}0.03$ and $0.10{\pm}0.04$ in Meishan sows, respectively. There was moderate genetic correlation between AP and WSI, while there were low genetic correlations between the other pairwise traits. The genetic correlations were positive for most of the pairwise traits, except for the one between AP and IISDLS. The results indicated that all traits except for AP were difficult to make genetic improvement by traditional selection methods due to low heritabilities and the favorable improvement of AP might result in unfavorable changes of IISDLS due to the trend of genetic antagonism.

• Journal of Genetic Medicine
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• 제7권1호
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• pp.16-23
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• 2010

많은 내분비 질환이 유전적 요소를 갖고 있다. 단일 유전자 질환에서는 유전적 요인이 주요 원인이나 다인자성 질환에서는 환경과 생활습관 등이 함께 병인으로 작용한다. 유전성 내분비 질환의 분자유전학적 병인에 대한 이해에 대하여 최근 많은 발전이 있어 왔으며 분자유전학적 기술의 응용으로 질환에 대한 이해와 이를 이용한 진단 및 유전 상담에 도움이 되고 있다. 유전학적 검사로 특정 질환의 돌연변이를 증명하는 것은 진단이 모호한 경우에서 정확한 진단과 산전 진단, 보인자 검사에 적용될 수 있다. 그러나 유전자 검사만으로 임신 중절과 관련된 산전 진단에 이용하는 데에는 신중을 기해야 한다.

• Asian-Australasian Journal of Animal Sciences
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• 제33권2호
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• pp.212-218
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• 2020

Objective: Agu pigs are indigenous to the Okinawa prefecture, which is the southernmost region of Japan. Agu pigs were exposed to a genetic bottleneck during the 20th century, due to the introduction of European pig breeds. The objective of this study was to elucidate the genetic structure of Agu pigs and to determine their relationships with those of five European breeds, two Chinese breeds and Ryukyu wild boar using microsatellite markers. Methods: A total of 203 DNA samples from 8 pig breeds were used in this study. Genotyping was performed using 21 microsatellite markers distributed across 17 chromosomes. Results: Numbers of effective alleles in Agu pigs were fewer than in European breeds and Ryukyu wild boar. Among domestic pigs, Agu pigs had the lowest heterozygosity (0.423) and highest inbreeding coefficient (F_IS = 0.202), indicating a severe loss of heterozygosity in Agu pigs possibly due to inbreeding. Neighbor-joining tree analysis was performed based on Reynolds' genetic distances, which clustered Agu pigs with Duroc pigs. However, principal component analysis revealed a unique genetic position of the Agu pig, and the second principal component separated Agu pigs from all other breeds. Structure analysis with the optimal assumption of seven groups (K = 7) indicated that Agu pigs form an independent cluster from the other breeds. In addition, high and significant F_ST values (0.235 to 0.413) were identified between Agu pigs and the other breeds. Conclusion: This study revealed a substantial loss of genetic diversity among Agu pigs due to inbreeding. Our data also suggest that Agu pigs have a distinctive genetic structure, although gene flows from European breeds were observed.

• 한국작물학회지
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• 제50권1호
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• pp.60-66
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• 2005

Pod shape of twenty soybean (Glycine max L. Merrill) genotypes was evaluated quantitatively by image analysis using elliptic Fourier descriptors and their principal components. The closed contour of each pod projection was extracted, and 80 elliptic Fourier coefficients were calculated for each contour. The Fourier coefficients were standardized so that they were invariant of size, rotation, shift, and chain code starting point. Then, the principal components on the standardized Fourier coefficients were evaluated. The cumulative contribution at the fifth principal component was higher than $95\%$, indicating that the first, second, third, fourth, and fifth principal components represented the aspect ratio of the pod, the location of the pod centroid, the sharpness of the two pod tips and the roundness of the base in the pod contour, respectively. Analysis of variance revealed significant genotypic differences in these principal components and seed number per pod. As the principal components for pod shape varied continuously, pod shape might be controlled by polygenes. It was concluded that principal component scores based on elliptic Fourier descriptors yield seemed to be useful in quantitative parameters not only for evaluating soybean pod shape in a soybean breeding program but also for describing pod shape for evaluating soybean germplasm.

• 산업공학
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• 제23권3호
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• pp.229-238
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• 2010

Virtual metrology (VM), a critical component of semiconductor manufacturing, is an efficient way of assessing the quality of wafers not actually measured. This is done based on a model between equipment sensor data (obtained for all wafers) and the quality characteristics of wafers actually measured. This paper considers principal component regression (PCR), partial least squares regression (PLSR), kernel PCR (KPCR), and kernel PLSR (KPLSR) as VM models. For each regression model, two cases are considered. One utilizes all explanatory variables in developing a model, and the other selects significant variables using the genetic algorithm (GA). The prediction performances of 8 regression models are compared for the short- and long-term etch process data. It is found among others that the GA-KPLSR model performs best for both types of data. Especially, its prediction ability is within the requirement for the short-term data implying that it can be used to implement VM for real etch processes.