• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8035-8040
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• 2014

Gastric cancer is the second after lung cause of cancer-related mortality in the world. Early detection and treatment can lead to a long survival time. Recently microarrays and next generation sequencing (NGS) have become very useful tools of comprehensive research into gastric cancer, facilitating the identification of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discovery to practical clinical benefits. Although there are many biomarkers and target agents, only a minority of patients are tested and treated accordingly. Microarray technology with maturity was established more than 10 years ago, and has been widely used in the study of functional genomics, systems biology, and genomes in medicine. Second generation sequencing technology is more recent, but development is very fast, and it has been applied to the genome, including sequencing and epigenetics and many aspects of functional genomics. Here we review insights gained from these studies regarding the technology of microarray and NGS, how to elucidate the molecular basis of gastric cancer and identify potential therapeutic targets, and how to analyse candidate genes. We also discuss the challenges and future directions of such efforts.

• Genomics & Informatics
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• v.14 no.2
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• pp.42-45
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• 2016

Since next-generation sequencing (NGS) technique was adopted into clinical practices, revolutionary advances in diagnosing rare genetic diseases have been achieved through translating genomic medicine into precision or personalized management. Indeed, several successful cases of molecular diagnosis and treatment with personalized or targeted therapies of rare genetic diseases have been reported. Still, there are several obstacles to be overcome for wider application of NGS-based precision medicine, including high sequencing cost, incomplete variant sensitivity and accuracy, practical complexities, and a shortage of available treatment options.

• Genomics & Informatics
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• v.8 no.2
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• pp.97-99
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• 2010

To allow for a quick conversion of the proprietary sequence data from various sequencing platforms, sequence format conversion toolkits are required that can be easily integrated into workflow systems. In this respect, a format conversion tool, as well as quality conversion tool would be the minimum requirements to integrate reads from different platforms. We have developed the Pyrus NGS Sequencing Format Converter, a simple software toolkit which allows to convert three kinds of Next Generation Sequencing reads, into commonly used fasta or fastq formats. The converter modules are all implemented, uniformly, in Java GUI modules that can be integrated in software applications for displaying the data content in the same format.

• The Korean Journal of Blood Transfusion
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• v.29 no.3
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• pp.310-319
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• 2018

Background: Research on next-generation sequencing (NGS)-based HLA typing is active. To resolve the phase ambiguity and long turn-around-time of conventional high resolution HLA typing, this study developed a NGS-based high resolution HLA typing method that can handle large-scale samples within an efficient testing time. Methods: For HLA NGS, the condition of nucleic acid extraction, library construction, PCR mechanism, and HLA typing with bioinformatics were developed. To confirm the accuracy of the NGS-based HLA typing method, the results of 192 samples HLA typed by SSOP and 28 samples typed by SBT compared to NGS-based HLA-A, -B and -DR typing. Results: DNA library construction through two-step PCR, NGS sequencing with MiSeq (Illumina Inc., San Diego, USA), and the data analysis platform were established. NGS-based HLA typing results were compatible with known HLA types from 220 blood samples. Conclusion: The NSG-based HLA typing method could handle large volume samples with high-throughput. Therefore, it would be useful for HLA typing of bone marrow donation volunteers.

• Genomics & Informatics
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• v.12 no.1
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• pp.2-11
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• 2014

After the initial enthusiasm of the human genome project, it became clear that without additional data pertaining to the epigenome, i.e., how the genome is marked at specific developmental periods, in different tissues, as well as across individuals and species-the promise of the genome sequencing project in understanding biology cannot be fulfilled. This realization prompted several large-scale efforts to map the epigenome, most notably the Encyclopedia of DNA Elements (ENCODE) project. While there is essentially a single genome in an individual, there are hundreds of epigenomes, corresponding to various types of epigenomic marks at different developmental times and in multiple tissue types. Unprecedented advances in next-generation sequencing (NGS) technologies, by virtue of low cost and high speeds that continue to improve at a rate beyond what is anticipated by Moore's law for computer hardware technologies, have revolutionized molecular biology and genetics research, and have in turn prompted innovative ways to reduce the problem of measuring cellular events involving DNA or RNA into a sequencing problem. In this article, we provide a brief overview of the epigenome, the various types of epigenomic data afforded by NGS, and some of the novel discoveries yielded by the epigenomics projects. We also provide ample references for the reader to get in-depth information on these topics.

• Journal of Life Science
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• v.31 no.4
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• Genomics & Informatics
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• v.18 no.1
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• pp.5.1-5.5
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• 2020

Highly pathogenic avian influenza (HPAI) viruses have caused severe respiratory disease and death in poultry and human beings. Although most of the avian influenza viruses (AIVs) are of low pathogenicity and cause mild infections in birds, some subtypes including hemagglutinin H5 and H7 subtype cause HPAI. Therefore, sensitive and accurate subtyping of AIV is important to prepare and prevent for the spread of HPAI. Next-generation sequencing (NGS) can analyze the full-length sequence information of entire AIV genome at once, so this technology is becoming a more common in detecting AIVs and predicting subtypes. However, an analysis pipeline of NGS-based AIV sequencing data, including AIV subtyping, has not yet been established. Here, in order to support the pre-processing of NGS data and its interpretation, we developed a user-friendly tool, named prediction of avian influenza virus subtype (PAIVS). PAIVS has multiple functions that support the pre-processing of NGS data, reference-guided AIV subtyping, de novo assembly, variant calling and identifying the closest full-length sequences by BLAST, and provide the graphical summary to the end users.

• 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.

• The Plant Pathology Journal
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• v.37 no.6
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• pp.521-532
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• 2021

Knowledge and better understanding of functions of the microbial community are pivotal for crop management. This study was conducted to study bacterial structures including Acidovorax species community structures and diversity from the watermelon cultivated soils in different regions of South Korea. In this study, soil samples were collected from watermelon cultivation areas from various places of South Korea and microbiome analysis was performed to analyze bacterial communities including Acidovorax species community. Next generation sequencing (NGS) was performed by extracting genomic DNA from 92 soil samples from 8 different provinces using a fast genomic DNA extraction kit. NGS data analysis results revealed that, total, 39,367 operational taxonomic unit (OTU), were obtained. NGS data results revealed that, most dominant phylum in all the soil samples was Proteobacteria (37.3%). In addition, most abundant genus was Acidobacterium (1.8%) in all the samples. In order to analyze species diversity among the collected soil samples, OTUs, community diversity, and Shannon index were measured. Shannon (9.297) and inverse Simpson (0.996) were found to have the highest diversity scores in the greenhouse soil sample of Gyeonggi-do province (GG4). Results from NGS sequencing suggest that, most of the soil samples consists of similar trend of bacterial community and diversity. Environmental factors play a key role in shaping the bacterial community and diversity. In order to address this statement, further correlation analysis between soil physical and chemical parameters with dominant bacterial community will be carried out to observe their interactions.

• Journal of Life Science
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• v.25 no.3
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• pp.349-356
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• 2015

Thanks to recent advances in next-generation sequencing (NGS) technology, diverse livestock species have been dissected at the genome-wide sequence level. As for cattle, there are currently four Korean indigenous breeds registered with the Domestic Animal Diversity Information System of the Food and Agricultural Organization of the United Nations: Hanwoo, Chikso, Heugu, and Jeju Heugu. These native genetic resources were recently whole-genome resequenced using various NGS technologies, providing enormous single nucleotide polymorphism information across the genomes. The NGS application further provided biological such that Korean native cattle are genetically distant from some cattle breeds of European origins. In addition, the NGS technology was successfully applied to detect structural variations, particularly copy number variations that were usually difficult to identify at the genome-wide level with reasonable accuracy. Despite the success, those recent studies also showed an inherent limitation in sequencing only a representative individual of each breed. To elucidate the biological implications of the sequenced data, further confirmatory studies should be followed by sequencing or validating the population of each breed. Because NGS sequencing prices have consistently dropped, various population genomic theories can now be applied to the sequencing data obtained from the population of each breed of interest. There are still few such population studies available for the Korean native cattle breeds, but this situation will soon be improved with the recent initiative for NGS sequencing of diverse native livestock resources, including the Korean native cattle breeds.