• Asian-Australasian Journal of Animal Sciences
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• v.32 no.3
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• pp.320-333
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• 2019

Objective: The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction. Methods: In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA). Results: The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle. Conclusion: Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.99-107
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• 2020

Fibromyalgia is a disorder characterized by the core symptom of chronic widespread pain, along with fatigue, sleep disturbances, mood changes, and cognitive difficulties. The etiology of fibromyalgia involves a combination of biological factors, such as genetic vulnerability, alterations in pain processing and stress response system ; psychological factors, such as anxiety, depression, anger, and perceived stress ; environmental factors, such as infections, febrile diseases, and trauma. Central sensitization, which is amplified in the process of sensory stimulation, has been emphasized as a key etiological factor, as supported by enhanced wind-up, delayed aftersensation, decreased nociceptive flexion reflex threshold and functional imaging studies. Several guidelines recommend that a multimodal approach be used to treat fibromyalgia, including both pharmacological and non-pharmacological treatments, tailored to each individual, and that clinicians should provide an intellectual framework through sufficient education and emphasis on the importance of self-management. The prevalence of mood disorders, anxiety disorders, and other psychiatric problems is 7-9 times higher in patients with fibromyalgia than in the general population ; moreover, the association between fibromyalgia and certain psychopathologies or sleep problems has also been suggested. Since psychiatric problems, with shared vulnerabilities and risk factors, interact with fibromyalgia bidirectionally and also affect the disease course, an integrated management approach is needed to determine the risk of comorbidities.

• Korean Journal of Environment and Ecology
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• v.35 no.6
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• pp.632-643
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• 2021

The objective of this study was to examine vegetation community structure and distribution of Fraxinus chiisanensis in Mt.Minjuji of Chungcheongbuk-do by setting up and surveying 8 plots (400 m² each). Mean Importance Value (MIV) of Fraxinus chiisanensis in 8 plots was 35.19% in average (ranging from 26.07~42.74%). Since it is the dominant species in all plots, it is expected to maintain the present vegetation structure. The analysis of the DBH (diameter at breast height) showed that the diameter of Fraxinus chiisanensis in Mt.Minjuji ranges from 2 to 43cm. The majority of Fraxinus chiisanensis is expected to maintain current state unless disturbance or rapid environmental change occurs. The Species Diversity (H') was 0.8498~1.0261, Evenness (J') was 0.8160~0.9256, Dominance Index (D) was 0.0789~0.1840, Maximum Diversity (H'max) was 1.0414~1.2041. The analysis of annual ring and radial growth showed that the average age of Fraxinus chiisanensis in Mt.Minjuji was 29.1years(ranging from 22~58years). The average annual radial growth of Fraxinus chiisanensis was the highest in community G with 5.84mm and the lowest in community B with 2.80mm. The similarity index analysis revealed that the similarity index between community B and E, C and F, H was the highest with 69.0%, and the similarity index between community E and F was the lowest with 29.6%. Both the area of Fraxinus chiisanensis community of Mt.Minjuji and its population size are very small. Therefore, this area needs to be designated as Forest Genetic Resource Reserve.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.557-566
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• 2022

The Japanese eel Anguilla japonica is a highly valued research object that is important for aquaculture in Asia, including the Republic of Korea. However, few studies have been conducted analyzing parentage using microsatellite markers derived from the Japanese eel. We acquired Japanese eel genome data using next generation sequencing technology, and constructed a draft genome comprising 1,087 Mbp. Using the Simple Sequence Repeat Identification Tool program, 444,724 microsatellites were identified. Of these, 1,842 microsatellites located in the 3' untranslated region, which are stably inherited, were finally selected. Ninety-six primers were selected to validate polymorphism at these microsatellites, and 9 primers were finally identified for multiplex analysis. Using multiplex polymerase chain reaction with three different fluorescence chemistries, we performed parentage analysis of an artificial Japanese eel population. CERVUS software was used to calculate the logarithm of the odds (LOD) scores and the confidence of the parentage assignments. The results presented here show that 83 out of 85 paternity cases were assigned at 95% confidence to a candidate father and mother with LOD scores ranging from 4.79 to 28.2. This study provided a microsatellite marker-based assay for parentage analysis of Japanese eels, which will be useful for selective breeding and genetic diversity studies.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.202-202
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• 2022

Recently days, soybean production in paddy field is increasing, from 4,422 ha in 2016 to 10,658 ha in 2021 in Korea. It is easy for Phytophthora stem and root rot (PSR) occurring in paddy field condition, when it is poorly drained soils with a high clay content, and temporary flooding and ponding. Therefore PSR resistant soybean cultivar is required. The objective of this study is to identify QTL region and candidate genes relating to PSR resistance of the race in main soybean cultivation area in Korea. 210 soybean materials including cultivars and germplasm were used for inoculation and genome-wide association study (GWAS). Inoculation was conducted using stem-scar method with 2 replications in 2-year for the race 3053 from Kimje and 3617 from Andong. 210 materials were genotyped with Soya SNP 180K chip, and structure analysis and association mapping were conducted with QTLMAX V2. The results of inoculation showed that survival ratio ranged from 0% to 96.7% and mean 9.7% for 3053 and ranged from 0% to 100% and mean 7.6% for 3617. Structure analysis showed linkage disequillibrium (LD) was decayed below r²=0.5 at 335kb of SNP distance. Significant SNPs (LOD>7.0) were identified in Chr 1, 2, 3, 4, 5, 11, 14, 15 for 3053 and Chr 1, 2, 3, 7, 10, 14 for 3617. Especially, LD blocks (AX-90455181;15,056,628bp~AX-90475572;15,298,872bp) in Chr 2 for 3053 and 3067 were duplicated. 29 genes were identified on these genetic regions including Glyma.02gl47000 relating to ribosome recycling factor and defense response to fungus in Soybase.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.4
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• pp.343-370
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• 2023

Developing improved wheat varieties is vital for global food security to meet the rising demand for food. Therefore, assessing the genetic diversity across wheat genotypes is crucial. This study examined the diversity of 168 durum wheat and 47 common wheat collections from 54 different countries using twelve agro-morphological parameters. Geumgang, a prominent Korean common wheat variety, was used as a control. Both qualitative and quantitative agronomical characteristics showed wide variations. Most durum wheats were shown to possess dense spikes (90%), while common wheats showed dense (40%) or loose (38%) spikes, with yellowish-white being the dominant spike color. The majority of the accessions were awned regardless of wheat type, yellowish-white being the main awn color. White or red kernels were produced, with white kernels dominating in both common (74%) and durum (79%) wheats. Days to heading (DH) and days to maturity (DM) were in the ranges of 166-215 and 208-250 days, respectively, while the culm length (CL), spike length (SL), and awn length (AL) were in the ranges of 53.67-163, 5.33-18.67, and 0.50-19.00 cm, respectively. Durum wheats possessed the shortest average DH, DM, and SL, while common wheat had the longest CL and AL (p < 0.05). Common wheats also exhibited the highest average one-thousand-kernel weight. Hierarchical cluster analysis, aided by principal component analysis, grouped the population into seven clusters with significant differences in their quantitative variables (p < 0.05). In conclusion, this research revealed diversity among common and durum wheat genotypes. Notably, 26 durum wheat and 17 common wheat accessions outperformed the control, offering the potential for developing early-maturing, high-yielding, and lodging-resistant wheat varieties.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Korean Journal of Plant Taxonomy
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• v.46 no.2
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• pp.256-266
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• 2016

A total of 13,000 individuals of Dendrobium moniliforme (L.) Sw. artificially propagated in laboratories and greenhouses were restored in their natural habitat of Bogildo Island, Wandogun, in the southern part of Korea in June of 2013. The growing conditions of the individuals were monitored for two years. The parental individuals for the restoration were obtained from a wild population in southern Korea, from which seeds were produced via artificial crossings. These seeds were germinated and cultivated in growing media and two-year-old plants were then grown in greenhouse beds. The genetic diversity among the propagated individuals was confirmed by examining DNA sequences of five regions of the chloroplast genome and the nuclear ITS region. The diversity values were as high as the average values of natural populations. All propagated individuals were transplanted into two different sites on Bogildo by research teams with local residents and national park rangers. After restoration, we counted and measured the surviving individuals, vegetative propagated stems, and growth rates in June of both 2014 and 2015. There was no human interference, and 97% of the individuals survived. The number of propagules increased by 227% in two years. In contrast, the average length of the stems decreased during the period. In addition, different survival and propagation rates were recorded depending on the host plants and the restored sites. The shaded sides of rock cliffs and the bark of Quercus salicina showed the best propagation rates, followed by the bark of Camellia japonica. A few individuals of D. moniliforme successfully flowered, pollinated, and fruited after restoration. Overall, our monitoring data over two years indicate that the restored individuals were well adapted and vigorously propagated at the restored sites. In order to prevent human disturbance of the restored sites, a CCTV monitoring system powered by a solar panel was installed after the restoration. In addition, a human surveillance system is operated by national park rangers with local residents.

• Korean Journal of Poultry Science
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• v.40 no.2
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• pp.139-145
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• 2013

There are several loci controlling the feather color of birds, of which one of the most studied is Extended black (E) encoding the melanocortin 1-receptor (MC1R). Mutations in this gene affect the relative distribution of eumelanin, phaeomelanin. The association of feather color and sequence polymorphism in the melanocortin 1-receptor (MC1R) gene was investigated using Korean native chicken H breed (H_PL) and 'Woorimatdag' commercial chickens (Woorimatdag_CC). In order to correlate gene mutation to Korean native chicken feather color, single nucleotide polymorphism (SNP) from MC1R gene sequence were investigated. A total of 307 birds from H_PL and Woorimatdag_CC were used. H_PL have black, black-brown feather color and Woorimatdag_CC have black with brown spots or brown with black spots. There are 6 SNPs in MC1R gene, locus T69C, C212T, A274G, G376A, G636A, T637C. 3 SNPs are nonsynonymous that change amino acid. But it is difficult to find correlation of feather color and polymorphisms. It will be needed to increase the population of Korean native chicken H breed and correlation analysis of genetic variation with feather colors.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.