• The Plant Pathology Journal
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• v.21 no.2
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• pp.172-173
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• 2005

Until now, occurrence of Rice black-streaked dwarf virus (RBSDV) is observed in Gyeongsang provinces, southeastern part of Korea. However, recently, the occurrence of RBSDV is increasing and spreading in Jeonra provinces including Gochang-gun, southwestern part of Korea. RBSDV infected plants showed typical symptoms including stunted, deformed leaves with white waxy or black-streaked swelling along the veins. We extracted viral genomic dsRNA from infected leaves and analyzed dsRNA pattern by polyacrylamide gel electrophoresis. Ten genomic segments with similar sized dsRNAs were observed. We also detected RBSDV by reverse transcription (RT)-PCR using specific primers for S10 from genomic dsRNA and observed amplified DNA fragment specific for RBSDV S10.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.509-516
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• 2001

As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8041-8045
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• 2016

Cervical cancer is one of the most common cancers in women worldwide. During their life time the vast majority of women become infected with human papillomavirus (HPV), but interestingly only a small portion develop cervical cancer and in the remainder infection regresses to a normal healthy state. Beyond HPV status, associated molecular characterization of disease has to be established. However, initial work suggests the existence of several different molecular classes, based on the biological features of differentially expressed genes in each subtype. This suggests that additional risk factors play an important role in the outcome of infection. Host genomic factors play an important role in the outcome of such complex or multifactor diseases such as cervical cancer and are also known to regulate the rate of disease progression. The aim of this review was to compile advances in the field of host genomics of HPV positive and negative cervical cancer and their association with clinical response.

• Journal of Preventive Medicine and Public Health
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• v.35 no.2
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• pp.83-91
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• 2002

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolutions both in bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. The paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization, primary pattern analysis, and machine learning algorithms will be presented. Use of integrated biochip informatics technologies, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.11
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• pp.1546-1550
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• 2006

The purpose of this study was to assess the genetic variation and establish the relationship amongst breeds and strains using 15 chicken specific microsatellite markers. A total of 285 unrelated DNA samples from four Korean native chicken strains (Black strain of Korean native chicken; KL, Red Brown strain of Korean native chicken; KR, Ogol strain of Korean native chicken; KS and Yellow Brown strain of Korean native chicken; KY) and three introduced chicken breeds (F strain of White Leghorn; LF, K strain of White Leghorn; LK, Rhode Island Red; RC and Cornish; CN) were genotyped to estimate within and between breed genetic diversity indices. All the loci analyzed in 15 microsatellite markers showed a polymorphic pattern and the number of alleles ranged from 5 to 14. The polymorphism information content (PIC) of UMA1019 was the highest (0.872) and that of ADL0234 was the lowest (0.562). The expected total heterozygosity (He) within breed and mean number of observed alleles ranged from 0.540 (LF) to 0.689 (KY), and from 3.47 (LK) to 6.07 (KR), respectively. The genetic variation of KR and KY were the highest and the lowest within Korean native strains, respectively. The genetic distance results showed that Korean native chicken strains were separated with the three introduced chicken breeds clustered into another group. The lowest distance (0.149) was observed between the KR and KL breeds and the highest distance (0.855) between the KR and LK breeds. The microsatellite polymorphism data were shown to be useful for assessing the genetic relationship between Korean native strains and other foreign breeds.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1005-1011
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• 2005

Widespread distributions of repetitive DNA elements in bacteria genomes are useful for analysis of genomes and should be exploited to differentiate food-borne pathogenic bacteria among and within species. Enterobacterial repetitive intergenic consensus (ERIC) sequence has been used for ERIC-PCR genomic fingerprinting to identify and differentiate bacterial strains from various environmental sources. ERIC-PCH genomic fingerprinting was applied to detect and differentiate four major Gram-negative food-borne bacterial pathogens, Esherichia coli, Salmonella, Shigella, and Vibrio. Target DNA fragments of pathogens were amplified by ERIC-PCR reactions. Dendrograms of subsequent PCR fingerprinting patterns for each strain were constructed, through which relative similarity coefficients or genetic distances between different strains were obtained numerically. Numerical comparisons revealed ERIC-PCR genotyping is effective for differentiation of strains among and within species of food-borne bacterial pathogens, showing ERIC-PCR fingerprinting methods can be utilized to differentiate isolates from outbreak and to determine their clonal relationships among outbreaks.

• Journal of Animal Reproduction and Biotechnology
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• v.38 no.1
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• pp.32-37
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• 2023

This study has evaluated the genomic estimated breeding value (GEBV) of the commercial Hanwoo population using the genomic best linear unbiased prediction (GBLUP) method and genomic information. Furthermore, it analyzed the accuracy and realized accuracy of the GEBV. 1,740 heads of the Hanwoo population which were analyzed using a single nucleotide polymorphism (SNP) Chip has selected as the test population. For carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS), the mean GEBVs estimated using the GBLUP method were 3.819, 0.740, -0.248, and 0.041, respectively and the accuracy of each trait was 0.743, 0.728, 0.737, and 0.765, respectively. The accuracy of the breeding value was affected by heritability. The accuracy was estimated to be low in EMA with low heritability and high in MS with high heritability. Realized accuracy values of 0.522, 0.404, 0.444, and 0.539 for CWT, EMA, BFT, and MS, respectively, showing the same pattern as the accuracy value. The results of this study suggest that the breeding value of each individual can be estimated with higher accuracy by estimating the GEBV using the genomic information of 18,499 reference populations. If this method is used and applied to individual selection in a commercial Hanwoo population, more precise and economical individual selection is possible. In addition, continuous verification of the GBLUP model and establishment of a reference population suitable for commercial Hanwoo populations in Korea will enable a more accurate evaluation of individuals.

• Genomics & Informatics
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• v.18 no.3
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• pp.30.1-30.7
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• 2020

The novel coronavirus pandemic that has originated from China and spread throughout the world in three months. Genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) predecessor, severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) play an important role in understanding the concept of genetic variation. In this paper, the genomic data accessed from National Center for Biotechnology Information (NCBI) through Molecular Evolutionary Genetic Analysis (MEGA) for statistical analysis. Firstly, the Bayesian information criterion (BIC) and Akaike information criterion (AICc) are used to evaluate the best substitution pattern. Secondly, the maximum likelihood method used to estimate of transition/transversions (R) through Kimura-2, Tamura-3, Hasegawa-Kishino-Yano, and Tamura-Nei nucleotide substitutions model. Thirdly and finally nucleotide frequencies computed based on genomic data of NCBI. The results indicate that general times reversible model has the lowest BIC and AICc score 347,394 and 347,287, respectively. The transition/transversions bias for nucleotide substitutions models varies from 0.56 to 0.59 in MEGA output. The average nitrogenous bases frequency of U, C, A, and G are 31.74, 19.48, 28.04, and 20.74, respectively in percentages. Overall the genomic data analysis of SARS-CoV-2, SARS-CoV, and MERS-CoV highlights the close genetic relationship.

• Food Science and Industry
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• v.52 no.3
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• pp.220-228
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• 2019

Rapid development of next-generation sequencing (NGS) technology is available to study microbes in genomic level. This NGS has been widely used in DNA/RNA sequencing for genome sequencing, metagenomics, and transcriptomics. The food microbiology area could be categorized into three groups. Food microbes including probiotics and food-borne pathogens are studied in genomic level using NGS for microbial genomics. While food fermentation or food spoilage are more complicated, their genomic study needs to be done with metagenomics using NGS for compositional analysis. Furthermore, because microbial response in food environments are also important to understand their roles in food fermentation or spoilage, pattern analysis of RNA expression in the specific food microbe is conducted using RNA-Seq. These microbial genomics, metagenomics, and transcriptomics for food fermentation and spoilage would extend our knowledge on effective utilization of fermenting bacteria for health promotion as well as efficient control of food-borne pathogens for food safety.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.1-9
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• 2001

scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences and information technology. The informatics revolutions both in clinical informatics and bioinformatics will change the current paradigm of biomedical sciences and practice of clinical medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. In this talk, 1 will describe how these technologies will in pact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine teaming algorithms will be presented. Issues of integrated biochip informatics technologies including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples from ongoing research activities in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.