• The Plant Pathology Journal
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• 제21권2호
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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.

• 정보처리학회논문지A
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• 제8A권4호
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• pp.509-516
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• 2001

생명 과학의 발전과 많은 게놈(genome) 프로젝트의 결과로 여러 종의 게놈 서열이 밝혀지고 있다. 생물체의 서열을 분석하는 방법은 전역정렬(global alignment), 지역정렬(local alignment) 등 여러 가지 방법이 있는데, 그 중 하나가 k-mer 분석이다. k-mer는 유전자의 염기 서열내의 길이가 k인 연속된 염기 서열로서 k-mer 분석은 염기서열이 가진 k-mer들의 빈도 분포나 대칭성 등을 탐색하는 것이다. 그런데 게놈의 염기 서열은 대용량 텍스트이고 k가 클 때 기존의 온메모리 알고리즘으로는 처리가 불가능하므로 효율적인 자료구조와 알고리즘이 필요하다. 스트링 B-트리는 패턴 일치(pattern matching)에 적합하고 외부 메모리를 지원하는 좋은 자료구조이다. 본 논문에서는 스트링 B-트리(string B-tree)를 k-mer 분석에 효율적인 구조로 개선하여, C. elegans 외의 30개의 게놈 서열에 대해 분석한다. k-mer들의 빈도 분포와 대칭성을 보여주기 위해 CGR(Chaotic Game Representation)을 이용한 가시화 시스템을 제시한다. 게놈 서열과 매우 유사한 서열 상의 어떤 부분을 시그니쳐(signature)라 하고, 높은 유사도를 가지는 최소 길이의 시그니쳐를 찾는 알고리즘을 제시한다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권18호
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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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• 제35권2호
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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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• 제19권11호
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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.

• 한국식품과학회지
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• 제37권6호
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• pp.1005-1011
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• 2005

본 연구에서는 높은 분리능을 가지고 있을 뿐만 아니라 실험의 재현성과 경제성의 측면에서도 많은 장점을 갖고 있는 ERIC DNA sequence를 응용한 ERIC-PCR을 이용하여 Salmonella, E. coli, Shigella, Vibrio 등 4속의 주요 그람 음성 식중독유발 세균들의 분리 동정 방법을 확립하고자 하였다. ERIC-PCR 결과, E. coli의 경우 0.3kb, 0.42kb 및 1.2kb의 band가 모든 균주에서 공통적으로 확인되었고, Salmonella속으로부터는 0.22kb, 0.4kb 및 0.7kb의 band가 증폭되었다. Shigella속은 모든 표준균주와 분리균주로부터 0.33kb와 1.25kb의 band가 증폭되었으며, S. sonnei의 경우 위의 주요 2개 band 이외에도 대부분의 균주에서 0.44kb, 2.0kb 및 3.05kb의 band가 증폭되어 다른 종의 Shigella와 구별되는 fingerprinting pattern을 나타내었다. 그리고 V. parahaemolyticus의 경우 표준균주와 분리균주 모두 0.51kb와 1.5kb의 band가 증폭되어 V. cholerae, V. mimicus 등과 같은 다른 종의 Vibrio와 구별되는 fingerprinting pattern을 나타내었다. 이와 같이 4속의 모든 식중독 균주마다 ERIC-PCR후 생성되는 fingerprinting pattern에서 3-5개의 공통적인 band가 증폭되는 것이 확인되어 이를 이용한 속 수준의 분리 동정과 이러한 주요 band들 이외의 부수적인 band들을 고려하여 종 수준까지의 분리도 가능함을 확인하였다. 따라서 본 연구의 결과는 ERIC 반복적 DNA 염기서열을 이용한 ERIC-PCR이 식중독균의 분리 동정 방법으로 사용될 수 있음을 확인하였으며, 나아가 더 많은 속(genus)의 식중독세균을 대상으로 한 새로운 분리 동정 방법을 확립하는데도 응용이 될 수 있을 것이다.

• 한국동물생명공학회지
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• 제38권1호
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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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• 제18권3호
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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.

• 식품과학과 산업
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• 제52권3호
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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.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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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.