• Genomics & Informatics
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• v.15 no.4
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• pp.178-182
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• 2017

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

• BMB Reports
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• v.53 no.6
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• pp.299-310
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• 2020

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2004.11a
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• pp.271-274
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• 2004

Nutritional genomics is a new field of study of how nutrition interacts with an individual's genome or individual responds to individual diets. Systematic approach of nutritional genomics will likely provide important clues about responders and non-responders. The current interest in personalizing health stems from the breakthroughs emerging in integrative technologies of genomics and epigenomics and the identification of genetic and epigentic diversity in individual's genetic make-up that are associated with variations in many aspects of health, including diet-related diseases. Microarray is a powerful screen system that is being also currently employed in nutritional research. Monitoring of gene expression at genome level is now possible with this technology, which allows the simultaneous assessment of the transcription of tens of thousands of genes and of their relative expression of pathological cells such tumor cells compared with that of normal cells. Epigenetic events such as DNA methylation can result in change of gene expression without involving changes in gene sequence. Recent developed technology of DNAarray-based methylation assay will facilitate wide study of epigenetic process in nutrigenomics. Some of the areas that would benefitfrom these technologies include identifying molecular targets (Biomarkers) for the risk and benefit assessment. These characterized biomarkers can reflect expose, response, and susceptibility to foods and their components. Furthermore the identified new biomarker perhaps can be utilized as a indicator of delivery system fur optimizing health.

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.277.1-277
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• 1999

No Abstract, See Full Text

• Genomics & Informatics
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• v.16 no.4
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• pp.36.1-36.3
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• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1351-1360
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• 2023

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.527-539
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• 2023

Pepper (Capsicum annuum L.) is an important vegetable and spice crop that has been cultivated worldwide. Pepper fruits have unique taste and aroma, providing a variety of antioxidants and compounds important for human health, which makes a high economic value. In addition, there is a high demand for new pepper varieties, according to consumer's preference. However, pepper is a recalcitrant plant for in vitro tissue and organ differentiation and plant regeneration, which makes it difficult to develop demanded varieties using newly developed technologies such as genetic engineering and gene editing. In this study, tissue culture and regeneration conditions were investigated using seven pepper varieties that were obtained from the core-collection of Seoul National University. We observed callus and bud induction and shoot formation using several media composition composed of different cytokinins and auxin concentrations. As a result, it was found that there were differences in callus induction and shoot formation of each variety depending on the hormone composition, and the highest regeneration was shown when the medium containing Zeatin Riboside and the petioles of seedlings were used. In particular, out of seven pepper varieties, CMV980 exhibited a higher regeneration efficiency (approximately 48%) than other varieties, followed by Yuwolcho. Therefore, this study provides CMV980 and Yuwolcho as good candidates that can be used for pepper transformation, which might contribute to the development of various varieties through gene editing technology in the future.

• Journal of Plant Biotechnology
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• v.39 no.1
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• pp.49-61
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• 2012

This review summarises the biology, discovery and applications of single nucleotide polymorphisms in complex polyploid crop genomes, with a focus on the important oilseed crop $Brassica$ $napus$. $Brassica$ $napus$ is an allotetraploid species, and along with soybean and oil palm is one of the top three most important oilseed crops globally. Current efforts are well underway to $de$ $novo$ assemble the $B.$ $napus$ genome, following the release of the related $B.$ $rapa$ 'A' genome last year. The next generation of genome sequencing, SNP discovery and analysis pipelines, and the associated challenges for this work in $B.$ $napus$, will be addressed. The biological applications of SNP technology for both evolutionary and molecular geneticists as well as plant breeders and industry are far-reaching, and will be invaluable to our understanding and advancement of the $Brassica$ crop species.

• 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.

• Genomics & Informatics
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• v.9 no.4
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• pp.173-180
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• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.