• Korean Journal of Clinical Laboratory Science
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• v.44 no.4
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• pp.167-177
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• 2012

Next-Generation Sequencing (NGS) is a term that means post-Sanger sequencing methods with high-throughput sequencing technologies. NGS parallelizes the sequencing process, producing thousands or millions of sequences at once. The latest NGS technologies use even single DNA molecule as a template and measures the DNA sequence directly via measuring electronic signals from the extension or degradation of DNA. NGS is making big impacts on biomedical research, molecular diagnosis and personalized medicine. The hospitals are rapidly adopting the use of NGS to help to patients understand treatment with sequencing data. As NGS equipments are getting smaller and affordable, many hospitals are in the process of setting up NGS platforms. In this review, the progress of NGS technology development and action mechanisms of representative NGS equipments of each generation were discussed. The key technological advances in the commercialized platforms were presented. As NGS platforms are a great concern in the healthcare area, the latest trend in the use of NGS and the prospect of NGS in the future in diagnosis and personalized medicine were also discussed.

• Journal of Life Science
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• v.25 no.3
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• pp.357-367
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• 2015

With the ongoing development of next-generation sequencing (NGS) platforms and advancements in the latest bioinformatics tools at an unprecedented pace, the ultimate goal of sequencing the human genome for less than $1,000 can be feasible in the near future. The rapid technological advances in NGS have brought about increasing demands for statistical methods and bioinformatics tools for the analysis and management of NGS data. Even in the early stages of the commercial availability of NGS platforms, a large number of applications or tools already existed for analyzing, interpreting, and visualizing NGS data. However, the availability of this plethora of NGS data presents a significant challenge for storage, analyses, and data management. Intrinsically, the analysis of NGS data includes the alignment of sequence reads to a reference, base-calling, and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection, and genome browsing. While the NGS technologies have allowed a massive increase in available raw sequence data, a number of new informatics challenges and difficulties must be addressed to improve the current state and fulfill the promise of genome research. This review aims to provide an overview of major NGS technologies and bioinformatics tools for NGS data analyses.

• Genomics & Informatics
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• v.13 no.3
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• pp.81-85
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• 2015

Molecular characterization technology in genetically modified organisms, in addition to how transgenic biotechnologies are developed now require full transparency to assess the risk to living modified and non-modified organisms. Next generation sequencing (NGS) methodology is suggested as an effective means in genome characterization and detection of transgenic insertion locations. In the present study, we applied NGS to insert transgenic loci, specifically the epidermal growth factor (EGF) in genetically modified rice cells. A total of 29.3 Gb (${\sim}72{\times}coverage$) was sequenced with a $2{\times}150bp$ paired end method by Illumina HiSeq2500, which was consecutively mapped to the rice genome and T-vector sequence. The compatible pairs of reads were successfully mapped to 10 loci on the rice chromosome and vector sequences were validated to the insertion location by polymerase chain reaction (PCR) amplification. The EGF transgenic site was confirmed only on chromosome 4 by PCR. Results of this study demonstrated the success of NGS data to characterize the rice genome. Bioinformatics analyses must be developed in association with NGS data to identify highly accurate transgenic sites.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.957-963
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• 2009

It is necessary for the resource management system to manage for the resource in distributed networking environment. Because of increasing the complexity of vast computer system and business environment, needs of RMS is increasing. Based on the common information model to use of objected oriented technology, through analysis of the reference model for the resource management system of the SNIA, we intend to implement the application program to manage the NGS system that consist of SSD and DRAM. To visualize, it is use the GUI Interface. It is possible for application program(Client) to detect and manage the system that consist of the NGS system. Also, status information that is divided into three cataloges(Minor/Major/Critical) can be displayed and it provide support of configuration functionality to manage devices.

• Korean Journal of Breeding Science
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• v.50 no.4
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• pp.364-377
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• 2018

Hexaploid wheat (common wheat/bread wheat) is one of the most important cereal crops in the world and a model for research of an allopolyploid plant with a large, highly repetitive genome. In the heritability of agronomic traits, variation in gene presence/absence plays an important role. However, there have been relatively few studies on the variation in gene presence/absence in crop species, including common wheat. Recently, a reference genome sequence of common wheat has been fully annotated and published. In addition, advanced next-generation sequencing (NGS) technology provides high quality genome sequences with continually decreasing NGS prices, thereby dawning full-scale wheat functional genomic studies in other crops as well as common wheat, in spite of their large and complex genomes. In this review, we provide information about the available tools and methodologies for wheat functional genomics research supported by NGS technology. The use of the NGS and functional genomics technology is expected to be a powerful strategy to select elite lines for a number of germplasms.

• Journal of Animal Environmental Science
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• v.21 no.3
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• pp.93-98
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• 2015

The objective of this study was to review application of next-generation sequencing (NGS) to investigate microbiome in the livestock sector. Since the 16S rRNA gene is used as a phylogenetic marker, unculturable members of microbiome in nature or managed environments have been investigated using the NGS technique based on 16S rRNA genes. However, few NGS studies have been conducted to investigate microbiome in the livestock sector. The 16S rRNA gene sequences obtained from NGS are classified to microbial taxa against the 16S rRNA gene reference database such as RDP, Greengenes and Silva databases. The sequences also are clustered into species-level OTUs at 97% sequence similarity. Microbiome similarity among treatment groups is visualized using principal coordinates analysis, while microbiome shared among treatment groups is visualized using a venn diagram. The use of the NGS technique will contribute to elucidating roles of microbiome in the livestock sector.

• Korean Journal of Veterinary Service
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• v.42 no.4
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• pp.217-225
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• 2019

To detect Single nucleotide polymorphisms (SNP) markers associated with Bovine viral diarrhea virus (BVDV) and Bovine respiratory syncytial virus (BRSV) S/P ratio in Korean Holstein dairy cattle, Genome-wide association study (GWAS) was performed using Illumina BovineSNP50 Beadchip. The number of phenotype data and genotype data were 107, and 294. respectively. Phenotype data were collected for four periods (0 week, 1 week, 4 week, 24 week) after having vaccinated (0 week no vaccinated period). A total of 36,257 SNPs was remained after quality control had been done by PLINK. The result of GWAS showed 6 SNP markers (BTB-01704243, BTB-01594395, ARS-BFGL-NGS-118070, ARS-BFGL-NGS-111365, BTA-65410-no-rs, Hapmap38331-BTA-61256) under BVDV and 4 SNP markers (ARS-BFGL-NGS-109861, Hapmap53701-rs29017064, ARS-BFGL-NGS-71055, BTA-11232-no-rs) under BRSV. And also, 10 candidate genes found through 10 SNP markers (TBX18, CEP162, PAFAH1B1, METTL16, BRCA1, RND2, POLK, ENSBTAG00000051724, ADAM18, NRG3).

• 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.

• Plant Breeding and Biotechnology
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• v.5 no.4
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• pp.269-281
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• 2017

With the continual development of genetically modified (GM) crops, it has become necessary to develop detailed and effective molecular characterization methods to select candidate events from a large pool of transformation events. Relative to traditional molecular analysis methods such as the polymerase chain reaction (PCR) and Southern blot hybridization, next generation sequencing (NGS) technology for whole-genome sequencing of complex crop genomes had proven comparatively useful for in-depth molecular characterization. In this study, four transformation events, including one in Bacillus thuringiensis (Bt)-resistant rice, one in resveratrol-producing rice, and two in beta-carotene-enhanced soybeans, were selected for molecular characterization. To merge NGS analysis and Southern blot-hybridization results, we confirmed the transgene insertion sites, insertion construction, and insertion numbers of these four transformation events. In addition, the read-coverage depth assessed by NGS analysis for inserted genes might provide consistent results in terms of inserted T-DNA numbers in case of complex insertion structures and highly duplicated donor genomes; however, PCR-based methods can produce incorrect conclusions. Our combined method provides an effective and complete analytical approach for whole-genome visual inspection of transformation events that require biosafety assessment.

• Korean Journal of Environmental Biology
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• v.36 no.2
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• pp.165-173
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• 2018

We sampled vomit of black-faced spoonbills(Platalea minor) during the brood-rearing season (from June 2011 to June 2014) at the Namdong reservoir in Incheon and analyzed the food components in the vomit using microscopy and next-generation sequencing (NGS). Microscopic observations primarily helped in identifying osteichthyes (bony fishes), crustaceans, and polychaetes. In particular, species belonging to the families Mugilidae and Gobiidae among the fish, and Macrophthalmus japonicas among the crustaceans, were observed at high frequency. Results of NGS analysis revealed the predominant presence of bony fish (42.58% of total reads) and crustaceans (40.75% of total reads), whereas others, such as polychaetes (12.66%), insects (0.24%), and unidentified species (3.78%), occurred in lower proportions. At the species level, results of NGS analysis revealed that Macrophthalmus abbreviates and Macrobrachium sp. among the crustaceans, and Acanthogobius hasta, Tridentiger obscurus, and Pterogobius zacalles among the bony fish, made up a high proportion of the total reads. These food species are frequently found at tidal flats in the Songdo and Sihwa lakes, emphasizing the importance of these areas as potential feeding sites of the black-faced spoonbill. Feed composition of the black-faced spoonbill, as evaluated by analyzing its vomit, differed when the evaluations were done by microscopic observation or by NGS analysis. Evaluation by microscopic observation is difficult and not error free, owing to the degradation of the samples to be analyzed; however, NGS analysis is more accurate, because it makes use of genetic information. Therefore, accurately analyzing food components from morphologically indistinguishable samples is possible by using genetic analysis.