• Clinical and Experimental Pediatrics
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• v.55 no.1
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• pp.6-10
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• 2012

Human puberty is a complex, coordinated biological process with multiple levels of regulations. The timing of puberty varies greatly in children and is influenced by both environmental and genetic factors. The key genes of pubertal onset, $KISS1$, $GPR54$, $GNRH1$ and $GNRHR$, may be major causal factors underlying gonadotropin-releasing hormone-dependent precocious puberty (GDPP). Two gain-of-function mutations in $KISS1$ and $GPR54$ have been identified recently as genetic causes of GDPP. $GNRH1$ and $GNRHR$ are also gene candidates for GDPP; however no mutations have been identified in these genes. Presently potential genetic causes like $LIN28B$ continues to appear; many areas of research await exploration in this context. In this review, I focus primarily on the genetic causes of GDPP.

• Journal of Forest and Environmental Science
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• v.25 no.3
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• pp.195-204
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• 2009

Agrobacterium-mediated genetic transformation has been widely used for the production of genetically modified transgenic plants to obtain specific desired traits. Most of the molecular mechanisms that underlie the transformation steps have been well elucidated over the years. However, a few steps, such as nuclear targeting, T-DNA integration, and Agrobacterium-plant proteins involved remain largely obscure and are still under extensive studies. This review describes the major steps involved in the molecular mechanism of Agrobacterium-mediated transformation and provides insight in the recent developments in studies on the Agrobacterium-mediated genetic transformation system. Some factors affecting the transformation efficiency are also briefly discussed.

• International Journal of Industrial Entomology and Biomaterials
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• v.1 no.1
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• pp.1-7
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• 2000

Early studies of the molecular biology of Bacillus thuringeinsis suggested that genetic manipulation of this species could create combinations of genes more useful than those known to occur in natural isolates. Breakthroughs that made these manipulations possible include the cloning of many genes encoding endotoxins, the development of transformation vectors, and various PCR techniques. This paper reviews several genetic factors such as promoters, a 5'mRNA stabilizing sequence, 3'transcription termination sequences, and helper proteins that have been used to enhance crystal protein synthesis, and shows how these genetic elements can be manipulated with new molecular tools to develop more efficacious strains of B. thuringiensis.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.859-870
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• 2015

Economic-traits of livestock are affected by environmental and genetic factors. We are interested in genetic factors that influence the economic-traits of Korean cattle. It is necessary to adjust environmental factors in order to enhance the accuracy of the genetic effect analysis. In this paper, we propose a statistical model of Korean cattle that exclude environmental breeding farm and age factors. We formulated an adjusted economic-trait value, and applied multifactor dimensionality reduction (MDR) method to data of before-and-after adjustment to identify major FABP4 genes. We were able to increase the accuracy of the analysis after adjustment and identify superior FABP4 genes that influence grade and fatty acid.

• Nutrition Research and Practice
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• v.10 no.3
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• pp.265-273
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• 2016

BACKGROUND/OBJECTIVES: The inhibitory effect of Hijikia fusiforme (HF) extracts on degenerative osteoarthritis was examined in primary cultured rat cartilage cells and a monosodium iodoacetate (MIA)-induced osteoarthritis rat model. MATERIALS/METHODS: In vitro, cell survival and the expression of matrix metalloproteinases (MMPs), collagen type I, collagen type II, aggrecan, and tissue inhibitor of metalloproteinases (TIMPs) was measured after $H_2O_2$ ($800{\mu}M$, 2 hr) treatment in primary chondrocytes. In vivo animal study, osteoarthritis was induced by intra-articular injection of MIA into knee joints of rats, and then RH500, HFE250 and HFE500 were administered orally once a day for 28 days. To determine the anti-inflammatory effects of HFE, nitric oxide (NO), prostaglandin $E_2$ ($PGE_2$) expression were measured. In addition, real-time PCR was performed to measure the genetic expression of MMPs, collagen type I, collagen type II, aggrecan, and TIMPs. RESULTS: In the in vitro assay, cell survival after $H_2O_2$ treatment was increased by HFE extract (20% EtOH). In addition, anabolic factors (genetic expression of collagen type I, II, and aggrecan) were increased by HFE extract (20% EtOH). However, the genetic expression of MMP-3 and 7, known as catabolic factors were significantly inhibited by treatment with HFE extract (20% EtOH). In the in vivo assay, anabolic factors (genetic expression of collagen type I, II, aggrecan, and TIMPs) were increased by oral administration of HFE extract. However, the genetic expression of MMP-3 and 7, known as catabolic factors, and production of NO and $PGE_2$ were significantly inhibited by treatment with oral administration of HFE extract. CONCLUSION: HFE extract inhibited articular cartilage degeneration through preventing extracellular matrix degradation and chondrocyte injury.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.6
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• pp.765-772
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• 2017

Objective: This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods: To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results: The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion: The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.1
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• pp.22-27
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• 2012

The experiment involved observations of 2,514 Holstein-Friesian cows to determine the effects of environmental factors (cow's age, calving season, weight and sex of calves, housing system) and genetic factors on gestation length in dairy cattle and the correlation between gestation length and other reproductive traits (calving ease, stillbirth rates and placental expulsion). Genetic parameters were estimated based on the sires of calved cows (indirect effect) and the sires of live-born calves (direct effect). The following factors were found to contribute to prolonged gestation: increasing cow's age, male fetuses and growing fetus weight. Optimal gestation length was determined in the range of 275-277 days based on calving ease and stillbirth rates. The heritability of gestation length was estimated at 0.201-0.210 by the direct effect and 0.055-0.073 by the indirect effect. The resulting genetic correlations suggest that the efforts to optimize (prolong) gestation length could exert an adverse influence on the breeding value of bulls by increasing perinatal mortality and calving difficulty. The standard errors of the investigated parameters were relatively high, suggesting that any attempts to modify gestation length for the purpose of improving calving ease and reducing stillbirth rates should be introduced with great caution.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.2
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• pp.303-308
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• 2002

Genetic markers engendered by genome projects drew enormous interest in quantitative genetics, but knowledge on genetic architecture of complex traits is limited. Complexities in genetics will not allow us to easily clarify relationship between genotypes and phenotypes for quantitative traits. Quantitative genetics guides an important way in facing such challenges. It is our exciting task to find genes that affect complex traits. In this paper, landmark research and future prospects are discussed on genetic parameter estimation and quantitative trait locus (QTL) mapping as major subjects of interest.