• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.102-107
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• 2007

Human Genome Project (HGP) could unveil the secrets of human being by a long script of genetic codes, which enabled us to get access to mine the cause of diseases more efficiently. Two wheels for HGP, bioinformatics and high throughput technology are essential techniques for the genomic medicine. While microarray platforms are still evolving, we can screen more than 500,000 genotypes at once. Even we can sequence the whole genome of an organism within a day. Because the future medicne will focus on the genetic susceptibility of individuals, we need to find genetic variations of each person by efficient genotyping methods.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

• Korean Journal of Microbiology
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• v.54 no.3
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• pp.188-199
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• 2018

Genomic epidemiology exploits various basic microbial research areas. High-throughput sequencing technologies dramatically have been expanding the number of microbial genome sequences available. Abundant genomic data provide an opportunity to perform strain typing more effectively, helping identify microbial species and strains at a higher resolution than ever before. Genomic epidemiology needs to find antimicrobial resistance genes in addition to standard genome annotations. Strain typing and antimicrobial resistance gene finding are static aspects of genomic epidemiology. Finding which hosts infected which other hosts requires the inference of transient transmission routes among infected hosts. The strain typing, antimicrobial resistance gene finding, and transmission tree inference would allow for better surveillance of microbial infectious diseases, which is one of the ultimate goals of genomic epidemiology. Among several high-throughput sequencing technologies, genomic epidemiology will benefit from the more portability and shorter sequencing time of the Oxford Nanopore Technologies's MinION, the third-generation sequencing technology. Here, this study reviewed computational methods for quantifying antimicrobial resistance genes and inferring disease transmission trees. In addition, the MinION's applications to genomic epidemiology were discussed.

• 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.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Horticultural Science & Technology
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• v.35 no.2
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• pp.149-164
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• 2017

Next generation sequencing (NGS) technologies have led to the rapid accumulation of genome sequences through whole-genome sequencing and re-sequencing of crop species. Genomic resources provide the opportunity for a new revolution in plant breeding by facilitating the dissection of complex traits. Among vegetable crops, reference genomes have been sequenced and assembled for several species in the Solanaceae and Cucurbitaceae families, including tomato, pepper, cucumber, watermelon, and melon. These reference genomes have been leveraged for re-sequencing of diverse germplasm collections to explore genome-wide sequence variations, especially single nucleotide polymorphisms (SNPs). The use of genome-wide SNPs and high-throughput genotyping methods has led to the development of new strategies for dissecting complex quantitative traits, such as genome-wide association study (GWAS). In addition, the use of multi-parent populations, including nested association mapping (NAM) and multiparent advanced generation intercross (MAGIC) populations, has helped increase the accuracy of quantitative trait loci (QTL) detection. Consequently, a number of QTL have been discovered for agronomically important traits, such as disease resistance and fruit traits, with high mapping resolution. The molecular markers for these QTL represent a useful resource for enhancing selection efficiency via marker-assisted selection (MAS) in vegetable breeding programs. In this review, we discuss current genomic resources and marker-trait association analysis to facilitate genome-assisted breeding in vegetable species in the Solanaceae and Cucurbitaceae families.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1515-1526
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• 2022

Eukaryotic chromatin is highly organized in the 3D nuclear space and dynamically regulated in response to environmental stimuli. This genomic organization is arranged in a hierarchical fashion to support various cellular functions, including transcriptional regulation of gene expression. Like other host cellular mechanisms, viral pathogens utilize and modulate host chromatin architecture and its regulatory machinery to control features of their life cycle, such as lytic versus latent status. Combined with previous research focusing on individual loci, recent global genomic studies employing conformational assays coupled with high-throughput sequencing technology have informed models for host and, in some cases, viral 3D chromosomal structure re-organization during infection and the contribution of these alterations to virus-mediated diseases. Here, we review recent discoveries and progress in host and viral chromatin structural dynamics during infection, focusing on a subset of DNA (human herpesviruses and HPV) as well as RNA (HIV, influenza virus and SARS-CoV-2) viruses. An understanding of how host and viral genomic structure affect gene expression in both contexts and ultimately viral pathogenesis can facilitate the development of novel therapeutic strategies.

• International Journal of Oral Biology
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• v.45 no.3
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• pp.77-83
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• 2020

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.

• 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.

• Parasites, Hosts and Diseases
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• v.47 no.2
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• pp.83-91
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• 2009

The completion of many malaria parasite genomes provides great opportunities for genomewide characterization of gene expression and high-throughput genotyping. Substantial progress in malaria genomics and genotyping has been made recently, particularly the development of various microarray platforms for large-scale characterization of the Plasmodium falciparum genome. Microarray has been used for gene expression analysis, detection of single nucleotide polymorphism (SNP) and copy number variation (CNV), characterization of chromatin modifications, and other applications. Here we discuss some recent advances in genetic mapping and genomic studies of malaria parasites, focusing on the use of high-throughput arrays for the detection of SNP and CNV in the P. falciparum genome. Strategies for genetic mapping of malaria traits are also discussed.