• BMB Reports
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• v.55 no.7
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• pp.360-360
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• 2022

• BMB Reports
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• v.55 no.4
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• pp.187-191
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• 2022

Obesity is caused by an imbalance between energy intake and energy expenditure. Exercise is attracting attention as one of the ways to treat obesity. Exercise induces 'beige adipogenesis' in white adipose tissue, increasing total energy expenditure via energy dissipation in the form of heat. Also, beige adipogenesis can be induced by treatment with a beta-adrenergic receptor agonist. We developed a Cidea-dual reporter mouse (Cidea-P2A-Luc2-T2A-tdTomato, Luciferase/tdTomato) model to trace and measure beige adipogenesis in vivo. As a result, both exercise and injection of beta-adrenergic receptor agonist induced beige adipogenesis and was detected through fluorescence and luminescence. We confirmed that exercise and beta-adrenergic receptor agonist induce beige adipogenesis in Cidea-dual reporter mouse, which will be widely used for detecting beige adipogenesis in vivo.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.119-130
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• 2020

With the current rapid growth and increase in the world's population, the demand for nutritious food and fibers and fuel will increase. Therefore, there is a serious need for the use of breeding programs with the full potential to produce high-yielding crops. However, existing breeding techniques are unable to meet the demand criteria even though genotyping techniques have significantly progressed with the discovery of molecular markers and next-generation sequencing tools, and conventional phenotyping techniques lag behind. Well-organized high-throughput plant phenotyping platforms have been established recently and developed in different parts of the world to address this problem. These platforms use several imaging techniques and technologies to acquire data for quantitative studies related to plant growth, yield, and adaptation to various types of abiotic or biotic stresses (drought, nutrient, disease, salinity, etc.). Phenotyping has become an impediment in genomics studies of plant breeding. In recent years, phenomics, an emerging domain that entails characterizing the full set of phenotypes in a given species, has appeared as a novel approach to enhance genomics data in breeding programs. Imaging techniques are of substantial importance in phenomics. In this study, the importance of current imaging technologies and their applications in plant phenotyping are reviewed, and their advantages and limitations in phenomics are highlighted.

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.317-323
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• 2018

The demand for crop production is increasingly becoming steeper due to the rapid population growth. As a result, breeding cycles should be faster than ever before. However, the current breeding methods cannot meet this requirement because traditional phenotyping methods lag far behind even though genotyping methods have been drastically developed with the advent of next-generation sequencing technology over a short period of time. Consequently, phenotyping has become a bottleneck in large-scale genomics-based plant breeding studies. Recently, however, phenomics, a new discipline involving the characterization of a full set of phenotypes in a given species, has emerged as an alternative technology to come up with exponentially increasing genomic data in plant breeding programs. There are many advantages for using new technologies in phenomics. Yet, the necessity of diverse man power and huge funding for cutting-edge equipment prevent many researchers who are interested in this area from adopting this new technique in their research programs. Currently, only a limited number of groups mostly in developed countries have initiated phenomic studies using high throughput methods. In this short article, we describe the strategies to compete with those advanced groups using limited resources in developing countries, followed by a brief introduction of high throughput phenotyping.

• Journal of Plant Biotechnology
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• v.43 no.4
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• pp.444-449
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• 2016

Deep rooting, which enables plants to extract water from greater soil depths, is a critical strategy for improving plant survival under water-deficient conditions. However, as it is difficult to observe intact root systems belowground, several techniques have been developed to screen deep- and shallow-rooting phenotypes in rice. Here, we introduce a simple and convenient method for deep- and shallow-rooting phenotyping using a unique combination of sand, soil, and plastic mesh netting. Vandana, a drought-tolerant rice variety, and Dongjin, a Korean japonica rice variety, were used to analyze root phenotypes. No significant differences in root length were observed in rice grown under irrigated conditions regardless of net position, whereas roots were significantly longer, and ratio of deep root (RDR) values were significantly higher in Vandana rice grown under semi-drought conditions. In summary, this simple and useful method represents a low-cost means of phenotyping the roots of rice and other crops grown in various-sized pots and at multiple plant growth stages.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

• BMB Reports
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• v.54 no.5
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• pp.266-271
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• 2021

Estrogen-related receptor γ (ERRγ), a member of the orphan nuclear receptor family, is a key mediator in cellular metabolic processes and energy homeostasis. Therefore, ERRγ has become an attractive target for treating diverse metabolic disorders. We recently reported that ERRγ acts as a negative regulator of osteoclastogenesis induced by receptor activator of nuclear factor-κB ligand (RANKL). In the present study, we explored the effects of an ERRγ-specific modulator, GSK5182, on ERRγ-regulated osteoclast differentiation and survival. Interestingly, GSK5182 increased ERRγ protein levels much as does GSK4716, which is an ERRγ agonist. GSK5182 inhibited osteoclast generation from bone-marrow-derived macrophages without affecting cytotoxicity. GSK5182 also attenuated RANKL-mediated expression of cFos and nuclear factor of activated T-cells cytoplasmic 1 (NFATc1), pivotal transcription factors for osteoclastogenesis. Arrested osteoclast differentiation was associated with reduced RANK expression, but not with the M-CSF receptor, c-Fms. GSK5182 strongly blocked the phosphorylation of IκBα, c-Jun N-terminal kinase, and extracellular signal-regulated kinase in response to RANKL. GSK5182 also suppressed NF-κB promoter activity in a dose-dependent manner. In addition to osteoclastogenesis, GSK5182 accelerated osteoclast apoptosis by caspase-3 activation. Together, these results suggest that GSK5182, a synthetic ERRγ modulator, may have potential in treating disorders related to bone resorption.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.10a
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• pp.12-12
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• 2017

• Toxicological Research
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• v.7 no.1
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• pp.1-12
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• 1991

The phenotyping of cytochrome P-450 in hepatic mivrosomes induced by phenytoin in the rats was carried out by using several monoclonal antibodies (MAbs) against specific P-450 isozymes. Phenytoin (180 mg/kg) was administered intrapritoneally for three consecutive days to the male Sprague-Dawley rats(100-120g). Solid phase radio-immunoassay showed higher binding affinity of MAb PB 2-66-3 and PCN 2-13-1 to the microsomes from phenytoin treated rats than those to from untreated rats, which was comparable to the level in phenobarbital induced rat hepatic microsomes.