• Clinical and Experimental Pediatrics
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• 제62권9호
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• pp.325-333
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• 2019

Allergic diseases, including allergic rhinitis, asthma, and atopic dermatitis, are common heterogeneous diseases that encompass diverse phenotypes and different pathogeneses. Phenotype studies of allergic diseases can facilitate the identification of risk factors and their underlying pathophysiology, resulting in the application of more effective treatment, selection of better treatment responses, and prediction of prognosis for each phenotype. In the early phase of phenotype studies in allergic diseases, artificial classifications were usually performed based on clinical features, such as triggering factors or the presence of atopy, which can result in the biased classification of phenotypes and limit the characterization of heterogeneous allergic diseases. Subsequent phenotype studies have suggested more diverse phenotypes for each allergic disease using relatively unbiased statistical methods, such as cluster analysis or latent class analysis. The classifications of phenotypes in allergic diseases may overlap or be unstable over time due to their complex interactions with genetic and encountered environmental factors during the illness, which may affect the disease course and pathophysiology. In this review, diverse phenotype classifications of allergic diseases, including atopic dermatitis, asthma, and wheezing in children, allergic rhinitis, and atopy, are described. The review also discusses the applications of the results obtained from phenotype studies performed in other countries to Korean children. Consideration of changes in the characteristics of each phenotype over time in an individual's lifespan is needed in future studies.

• BMB Reports
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• 제43권2호
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• pp.79-90
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• 2010

Mouse models are crucial for the functional annotation of human genome. Gene modification techniques including gene targeting and gene trap in mouse have provided powerful tools in the form of genetically engineered mice (GEM) for understanding the molecular pathogenesis of human diseases. Several international consortium and programs are under way to deliver mutations in every gene in mouse genome. The information from studying these GEM can be shared through international collaboration. However, there are many limitations in utility because not all human genes are knocked out in mouse and they are not yet phenotypically characterized by standardized ways which is required for sharing and evaluating data from GEM. The recent improvement in mouse genetics has now moved the bottleneck in mouse functional genomics from the production of GEM to the systematic mouse phenotype analysis of GEM. Enhanced, reproducible and comprehensive mouse phenotype analysis has thus emerged as a prerequisite for effectively engaging the phenotyping bottleneck. In this review, current information on systematic mouse phenotype analysis and an issue-oriented perspective will be provided.

• 원예과학기술지
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• 제33권4호
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• pp.559-565
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• 2015

The rind phenotype of watermelon fruits is an important agronomic characteristic in the watermelon market. Inheritance and linkage analyses were performed for three rind-related traits that together determine the rind phenotype: foreground stripe pattern, rind background color, and depth of rind color. The inheritance of the foreground stripe pattern was analyzed using three different $F_2$ populations, showing that the striped pattern is dominant over the non-striped pattern. The inheritance analysis of the rind background color was performed using $F_2$ populations of the '10909' and '109905', and the depth of rind color was analyzed using $F_2$ populations of the '90509' and '109905'. Yellow color was found to be dominant over green color, and a deep color was dominant over the standard color. Linkage analysis of the three traits was conducted using three $F_2$ populations in which two traits were segregating. Each pair of traits was inherited independently, which demonstrated that the three traits are not linked. Therefore, we propose a three-locus model for the determination of rind phenotype, providing novel insight that rind phenotype is determined by the combination of three genetically independent loci.

• Translational and Clinical Pharmacology
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• 제25권3호
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• pp.147-152
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• 2017

This study focused on the role of cytochrome P450 2D6 (CYP2D6) genotypes to predict phenotypes in the metabolism of dextromethorphan. CYP2D6 genotypes and metabolic ratios (MRs) of dextromethorphan were determined in 201 Koreans. Unsupervised clustering algorithms, hierarchical and k-means clustering analysis, and color visualizations of CYP2D6 activity were performed on a subset of 130 subjects. A total of 23 different genotypes were identified, five of which were observed in one subject. Phenotype classifications were based on the means, medians, and standard deviations of the log MR values for each genotype. Color visualization was used to display the mean and median of each genotype as different color intensities. Cutoff values were determined using receiver operating characteristic curves from the k-means analysis, and the data were validated in the remaining subset of 71 subjects. Using the two highest silhouette values, the selected numbers of clusters were three (the best) and four. The findings from the two clustering algorithms were similar to those of other studies, classifying $^*5/^*5$ as a lowest activity group and genotypes containing duplicated alleles (i.e., $CYP2D6^*1/^*2N$) as a highest activity group. The validation of the k-means clustering results with data from the 71 subjects revealed relatively high concordance rates: 92.8% and 73.9% in three and four clusters, respectively. Additionally, color visualization allowed for rapid interpretation of results. Although the clustering approach to predict CYP2D6 phenotype from CYP2D6 genotype is not fully complete, it provides general information about the genotype to phenotype relationship, including rare genotypes with only one subject.

• Genomics & Informatics
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• 제12권4호
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• pp.289-292
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• 2014

Next-generation sequencing (NGS) is widely used to identify the causative mutations underlying diverse human diseases, including cancers, which can be useful for discovering the diagnostic and therapeutic targets. Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. In this study, in order to support defining the recurrent mutations or phenotype-specific mutations from NGS data of a group of cancers with diverse phenotypes, we aimed to develop a user-friendly tool, named mutation arranger for defining phenotype-related SNV (MAP). MAP is a user-friendly program with multiple functions that supports the determination of recurrent or phenotype-specific mutations and provides graphic illustration images to the users. Its operation environment, the Microsoft Windows environment, enables more researchers who cannot operate Linux to define clinically meaningful mutations with NGS data from cancer cohorts.

• 한국산업정보학회논문지
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• 제25권5호
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• pp.83-90
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• 2020

본 논문에서는 콩/벼 종자의 이미지에서 표현체 정보인 종피색, 길이, 면적, 둘레, 응집도 등의 데이터를 추출하고 가시화하는 웹 기반 종자 표현체 가시화 지원시스템을 제안한다. 본 시스템은 종자에서 추출된 데이터를 체계적으로 데이터베이스에 저장하고, 데이터테이블과 차트를 이용하여 연구자의 데이터 분석을 용이하게 하는 웹 기반 사용자 인터페이스를 제공한다. 기존의 종자 특성 연구는 사람이 수작업으로 종자의 특성을 측정하였지만, 본 논문에서 개발한 시스템을 이용하여 간단히 연구자가 분석할 종자 이미지를 업로드하고 영상 처리 후 종자의 수치 데이터를 얻을 수 있다. 제안된 시스템이 종자 특성 연구에 활용이 되면 시간적 효율성을 얻을 수 있고 공간적 제약을 제거할 수 있을 것으로 기대되며, 표현체의 특성 분석 과정에서 연구 성과의 체계적인 관리와 특성의 가시화를 통한 분석이 용이할 것이다.

• Nutrition Research and Practice
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• 제6권2호
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• pp.120-125
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• 2012

The aim of this study was to investigate the influencing factors that characterize low density lipoprotein (LDL) phenotype and the levels of LDL particle size in healthy Korean women. In 57 healthy Korean women (mean age, $57.4{\pm}13.1$ yrs), anthropometric and biochemical parameters such as lipid profiles and LDL particle size were measured. Dietary intake was estimated by a developed semi-quantitative food frequency questionnaire. The study subjects were divided into two groups: LDL phenotype A (mean size: $269.7{\AA}$, n = 44) and LDL phenotype B (mean size: $248.2{\AA}$, n = 13). Basic characteristics were not significantly different between the two groups. The phenotype B group had a higher body mass index, higher serum levels of triglyceride, total-cholesterol, LDL-cholesterol, apolipoprotein (apo)B, and apoCIII but lower levels of high density lipoprotein (HDL)-cholesterol and LDL particle size than those of the phenotype A group. LDL particle size was negatively correlated with serum levels of triglyceride (r = -0.732, $P$ < 0.001), total-cholesterol, apoB, and apoCIII, as well as carbohydrate intake (%En) and positively correlated with serum levels of HDL-cholesterol and ApoA1 and fat intake (%En). A stepwise multiple linear regression analysis revealed that carbohydrate intake (%En) and serum triglyceride levels were the primary factors influencing LDL particle size ($P$ < 0.001, $R^2$ = 0.577). This result confirmed that LDL particle size was closely correlated with circulating triglycerides and demonstrated that particle size is significantly associated with dietary carbohydrate in Korean women.

• Genomics & Informatics
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• 제16권4호
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• pp.38.1-38.3
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• 2018

Gene-gene interaction (GGI) analysis is known to play an important role in explaining missing heritability. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in a case-control design. In this study, we developed "Hierarchical structural CoMponent analysis of Gene-Gene Interactions" (HisCoM-GGI) software for GGI analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between genes and single nucleotide polymorphisms (SNPs), enabling both gene-level and SNP-level interaction analysis in a single model. Furthermore, this software accepts various types of genomic data and supports data management and multithreading to improve the efficiency of genome-wide association study data analysis. We expect that HisCoM-GGI software will provide advanced accessibility to researchers in genetic interaction studies and a more effective way to understand biological mechanisms of complex diseases.

• Genomics & Informatics
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• 제16권4호
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• pp.33.1-33.9
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• 2018

Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases. To find out how genes are related to disease, we need to understand not only the simple relationship of genotypes but also the way they are related to phenotype. Multi-block data, which is a summation form of variable sets, is used for enhancing the analysis of the relationships of different blocks. By identifying relationships through a multi-block data form, we can understand the association between the blocks in comprehending the correlation between them. Several statistical analysis methods have been developed to understand the relationship between multi-block data. In this paper, we will use generalized canonical correlation methodology to analyze multi-block data from the Korean Association Resource project, which has a combination of single nucleotide polymorphism blocks, phenotype blocks, and disease blocks.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 2003년도 정기총회 및 학술발표회
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• pp.60-60
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• 2003

GSH-dependent glutaredoxinl (Grxl) was characterized in Dictyostelium discoideum. After starvation, the mRNA levels of grx1 gene increased during aggregation, thereafter decreased up to tip formation and increased again during culmination. To investigate the function of Grxl, the protein was overexpressed in D. discoideum using actinl5 promoter, The phenotype analysis on Grxl-overexpressed cells showed the maintenance of slug stage for a long period and delayed culmination under dark condition. To corroborate these phenotype by the enzyme, the two mutant forms of Grxl (C21S and C24S) were overexpressed in D. discoideum. The phenotype of two mutant cells represented no slug formation and the early culmination on dark condition. These results indicate that Grxl might regulate the transition from slug to culminant in darkness.