• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.24 no.1
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• pp.1-6
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• 2021

Next-generation sequencing (NGS) technologies have changed the process of genetic diagnosis from a gene-by-gene approach to syndrome-based diagnostic gene panel sequencing (DPS), diagnostic exome sequencing (DES), and diagnostic genome sequencing (DGS). A priori information on the causative genes that might underlie a genetic condition is a prerequisite for genetic diagnosis before conducting clinical NGS tests. Theoretically, DPS, DES, and DGS do not require any information on specific candidate genes. Therefore, clinical NGS tests sometimes detect disease-related pathogenic variants in genes underlying different conditions from the initial diagnosis. These clinical NGS tests are expensive, but they can be a cost-effective approach for the rapid diagnosis of rare disorders with genetic heterogeneity, such as the glycogen storage disease, familial intrahepatic cholestasis, lysosomal storage disease, and primary immunodeficiency. In addition, DES or DGS may find novel genes that that were previously not linked to human diseases.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.23 no.2
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• pp.1-7
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• 2023

Inherited metabolic disorders (IMD) are a group of disorders involving various metabolic pathways. Genetic diagnosis of IMD has been challenging because of extremely heterogeneous nature and extensive laboratory and/or phenotype overlap. Conventional genetic diagnosis was a gene-by-gene approach that needs a priori information on the causative genes that might underlie the IMD. Recent implementation of next-generation sequencing (NGS) technologies has changed the process of genetic diagnosis from a gene-by-gene approach to simultaneous analysis of targeted genes possibly associated with the IMD using gene panels or using whole exome/genome sequencing (WES/WGS) covering entire human genes. Clinical NGS tests can be a cost-effective approach for the rapid diagnosis of IMD with genetic heterogeneity and are becoming standard diagnostic procedures.

• Genomics & Informatics
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• v.19 no.4
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• pp.41.1-41.10
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• 2021

In addition to mutations and copy number alterations, gene fusions are commonly identified in cancers. In thyroid cancer, fusions of important cancer-related genes have been commonly reported; however, extant panels do not cover all clinically important gene fusions. In this study, we aimed to develop a custom RNA-based sequencing panel to identify the key fusions in thyroid cancer. Our ThyChase panel was designed to detect 87 types of gene fusion. As quality control of RNA sequencing, five housekeeping genes were included in this panel. When we applied this panel for the analysis of fusions containing reference RNA (HD796), three expected fusions (EML4-ALK, CCDC6-RET, and TPM3-NTRK1) were successfully identified. We confirmed the fusion breakpoint sequences of the three fusions from HD796 by Sanger sequencing. Regarding the limit of detection, this panel could detect the target fusions from a tumor sample containing a 1% fusion-positive tumor cellular fraction. Taken together, our ThyChase panel would be useful to identify gene fusions in the clinical field.

• Journal of Genetic Medicine
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• v.20 no.2
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• pp.31-38
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• 2023

Rare diseases, even though defined as fewer than 20,000 in South Korea, with over 8,000 rare Mendelian disorders having been identified, they collectively impact 6-8% of the global population. Many of the rare diseases pose significant challenges to patients, patients' families, and the healthcare system. The diagnostic journey for rare disease patients is often lengthy and arduous, hampered by the genetic diversity and phenotypic complexity of these conditions. With the advent of next-generation sequencing technology and clinical implementation of exome sequencing (ES) and genome sequencing (GS), the diagnostic rate for rare diseases is 25-50% depending on the disease category. It is also allowing more rapid new gene-disease association discovery and equipping us to practice precision medicine by offering tailored medical management plans, early intervention, family planning options. However, a substantial number of patients remain undiagnosed, and it could be due to several factors. Some may not have genetic disorders. Some may have disease-causing variants that are not detectable or interpretable by ES and GS. It's also possible that some patient might have a disease-causing variant in a gene that hasn't yet been linked to a disease. For patients who remain undiagnosed, reanalysis of existing data has shown promises in providing new molecular diagnoses achieved by new gene-disease associations, new variant discovery, and variant reclassification, leading to a 5-10% increase in the diagnostic rate. More advanced approach such as long-read sequencing, transcriptome sequencing and integration of multi-omics data may provide potential values in uncovering elusive genetic causes.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3187-3190
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• 2013

Background: Epidermal growth factor receptor (EGFR) is a transmembrane receptor which contributes to many processes involved in cell survival, proliferation and inhibits apoptosis, that may lead to cancer development. Gastric cancer is one of the most common diseases of digestive system that has low 5-year-survival. The aim of this research was to determine the significance of EGFR tyrosine kinase domain gene polymorphisms in gastric cancer in Iran. Materials and Methods: In the present study, 83 patients with gastric cancer and 40 normal subjects were investigated for EGFR gene polymorphisms in exons 18-21 by PCR-SSCP. Then, DNA sequencing was conducted for different mobility shift bands. Finally the data were statistically analyzed using the chi-2 test and the SPSSver.16 program. Results: Exon 18 of EGFR gene showed three different bands in SSCP pattern and DNA sequencing displayed one mutation. SSCP pattern of Exons 19 and 21 did not show different migration bands. Exon 20 of EGFR gene revealed multiple migrate bands in SSCP pattern. DNA sequencing displayed 2 mutations in this exon: one mutation was caused amino acid change and another mutation was silent. Conclusion: It may be that EGFR tyrosine kinase gene polymorphisms differ between populations and screening could be useful in gastric cancer patients who might benefit from tyrosine kinase inhibitor therapy.

• 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.

• Genomics & Informatics
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• v.20 no.3
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• pp.28.1-28.7
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• 2022

We described a clinical, laboratory, and genetic presentation of a pathogenic variant of the CYP1B1 gene through a report of a case of primary congenital glaucoma and a trio analysis of this candidate variant in the family with the Sanger sequencing method and eventually completed our study with the secondary/incidental findings. This study reports a rare case of primary congenital glaucoma, an 8-year-old female child with a negative family history of glaucoma and uncontrolled intraocular pressure. This case's whole-exome sequencing data analysis presents a homozygous pathogenic single nucleotide variant in the CYP1B1 gene (NM_000104:exon3:c.G1103A:p.R368H). At the same time, this pathogenic variant was obtained as a heterozygous state in her unaffected father but not her mother. The diagnosis was made based on molecular findings of whole-exome sequencing data analysis. Therefore, the clinical reports and bioinformatics findings supported the relation between the candidate pathogenic variant and the disease. However, it should not be forgotten that primary congenital glaucoma is not peculiar to the CYP1B1 gene. Since the chance of developing autosomal recessive disorders with low allele frequency and unrelated parents is extraordinary in offspring. However, further data analysis of whole-exome sequencing and Sanger sequencing method were applied to obtain the type of mutation and how it was carried to the offspring.

• Genomics & Informatics
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• v.15 no.4
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• pp.128-135
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• 2017

As next-generation sequencing technologies have advanced, enormous amounts of whole-genome sequence information in various species have been released. However, it is still difficult to assemble the whole genome precisely, due to inherent limitations of short-read sequencing technologies. In particular, the complexities of plants are incomparable to those of microorganisms or animals because of whole-genome duplications, repeat insertions, and Numt insertions, etc. In this study, we describe a new method for detecting misassembly sequence regions of Brassica rapa with genotyping-by-sequencing, followed by MadMapper clustering. The misassembly candidate regions were cross-checked with BAC clone paired-ends library sequences that have been mapped to the reference genome. The results were further verified with gene synteny relations between Brassica rapa and Arabidopsis thaliana. We conclude that this method will help detect misassembly regions and be applicable to incompletely assembled reference genomes from a variety of species.

• Animal Bioscience
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• v.36 no.2_spc
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• pp.364-373
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• 2023

The gastrointestinal (GI) tract of ruminants contains diverse microbes that ferment various feeds ingested by animals to produce various fermentation products, such as volatile fatty acids. Fermentation products can affect animal performance, health, and well-being. Within the GI microbes, the ruminal microbes are highly diverse, greatly contribute to fermentation, and are the most important in ruminant nutrition. Although traditional cultivation methods provided knowledge of the metabolism of GI microbes, most of the GI microbes could not be cultured on standard culture media. By contrast, amplicon sequencing of 16S rRNA genes can be used to detect unculturable microbes. Using this approach, ruminant nutritionists and microbiologists have conducted a plethora of nutritional studies, many including dietary interventions, to improve fermentation efficiency and nutrient utilization, which has greatly expanded knowledge of the GI microbiota. This review addresses the GI content sampling method, 16S rRNA gene amplicon sequencing, and bioinformatics analysis and then discusses recent studies on the various factors, such as diet, breed, gender, animal performance, and heat stress, that influence the GI microbiota and thereby ruminant nutrition.

• Genomics & Informatics
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• v.11 no.4
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• pp.191-199
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• 2013

High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.