• BMB Reports
• /
• v.49 no.12
• /
• pp.662-670
• /
• 2016

The human oral cavity contains a highly personalized microbiome essential to maintaining health, but capable of causing oral and systemic diseases. Thus, an in-depth definition of "healthy oral microbiome" is critical to understanding variations in disease states from preclinical conditions, and disease onset through progressive states of disease. With rapid advances in DNA sequencing and analytical technologies, population-based studies have documented the range and diversity of both taxonomic compositions and functional potentials observed in the oral microbiome in healthy individuals. Besides factors specific to the host, such as age and race/ethnicity, environmental factors also appear to contribute to the variability of the healthy oral microbiome. Here, we review bioinformatic techniques for metagenomic datasets, including their strengths and limitations. In addition, we summarize the interpersonal and intrapersonal diversity of the oral microbiome, taking into consideration the recent large-scale and longitudinal studies, including the Human Microbiome Project.

• CELLMED
• /
• v.3 no.2
• /
• pp.11.1-11.2
• /
• 2013

Advances in individual genome sequencing technology and next generation sequencing technology have allowed for widespread research of human genome, which would give us opportunities not only to change our focus from the experience-based Korean medicine including typology and Sasang constitution to the evidence-based Korean medicine but to provide effective tailored medical care and Tang theory.

• Journal of Veterinary Clinics
• /
• v.32 no.1
• /
• pp.62-68
• /
• 2015

There is no reliable indicator available for the diagnosis of horse laminitis, although the disease is common and costly. This study was performed to develop a specific diagnostic biomarker for laminitis. We have identified 33 differentially expressed proteins in plasma of a horse suffering laminitis that is experimentally induced by an overdose of oligofructose, in comparison with normal horse plasma. Among the proteins, myosin-9 mRNA was found in RNA sequencing analysis to be expressed specifically in laminitis tissues compared to other horse tissues. It is thus suggested that expression of plasma myosin-9 may be used for the diagnosis of equine laminitis.

• Journal of Plant Biotechnology
• /
• v.46 no.2
• /
• pp.71-78
• /
• 2019

The objective of this study was to use 'Danta PR', NGS (Next Generation Sequencing) technology for genome resequencing to develop polymorphic makers between Chinese oriental melon, 'Hyangseo 1' and Korean oriental melon. From the resequencing data that covered about 81 times of the genome size, 104,357 of SSR motifs and Indel, and 1,092,436 of SNPs were identified. 299 SSR and 307 Indel markers were chosen to cover each chromosome with 25 markers. These markers were subsequently used to identify genotypes of 'Danta PR' BC1 (F1 x 'Danta PR') population and a genetic linkage map was constructed. SSR, Indel, and SNPs identified in this study would be useful as a breeding tool to develop new oriental melon varieties.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.31-36
• /
• 2021

RNA sequencing (RNA-Seq) is a technology that facilitates transcriptome analysis using next-generation sequencing (NSG) tools. Information on the quantity and sequences of RNA is vital to relate our genomes to functional protein expression. RNA-Seq data are characterized as being high-dimensional in that the number of variables (i.e., transcripts) far exceeds the number of observations (e.g., experiments). Given the wide range of dimensionality reduction techniques, it is not clear which is best for RNA-Seq data analysis. In this paper, we study the effect of three dimensionality reduction techniques to improve the classification of the RNA-Seq dataset. In particular, we use PCA, SVD, and SOM to obtain a reduced feature space. We built nine classification models for a cancer dataset and compared their performance. Our experimental results indicate that better classification performance is obtained with PCA and SOM. Overall, the combinations PCA+KNN, SOM+RF, and SOM+KNN produce preferred results.

• Journal of Genetic Medicine
• /
• v.19 no.2
• /
• pp.57-62
• /
• 2022

Systemic autoinflammatory diseases (SAIDs) are characterized by unprovoked inflammatory episodes such as recurrent/periodic fever, serositis, skin lesions, abdominal symptoms, arthritis/arthralgia, and central nervous system involvement. Genetic diagnosis of SAIDs has been challenging because disease manifestations overlap among themselves and with other immunological disease categories, such as infection and autoimmune diseases. However, the advent of next-generation sequencing (NGS) technologies and expanding knowledge about the innate immunity and inflammation have made the routine genetic diagnosis of SAIDs possible. Here, we review the recurrent/periodic fevers, other recently identified autoinflammatory diseases, and type I interferonopathies, and discuss the clinical usefulness of NGS targeted sequencing for SAIDs, and recent advance of understandings for this heterogeneous disease group as for underlying primary immunodeficiency.

• Genomics & Informatics
• /
• v.17 no.4
• /
• pp.42.1-42.6
• /
• 2019

Robust identification of genetic alterations is important for the diagnosis and subsequent treatment of tumors. Screening for genetic alterations using tumor tissue samples may lead to biased interpretations because of the heterogeneous nature of the tumor mass. Liquid biopsy has been suggested as an attractive tool for the non-invasive follow-up of cancer treatment outcomes. In this study, we aimed to verify whether the mutations identified in primary tumor tissue samples could be consistently detected in plasma cell-free DNA (cfDNA) by digital polymerase chain reaction (dPCR). We first examined the genetic alteration profiles of three colorectal cancer (CRC) tissue samples by targeted next-generation sequencing (NGS) and identified 11 non-silent amino acid changes across six cancer-related genes (APC, KRAS, TP53, TERT, ARIDIA, and BRCA1). All three samples had KRAS mutations (G12V, G12C, and G13D), which were well-known driver events. Therefore, we examined the KRAS mutations by dPCR. When we examined the three KRAS mutations by dPCR using tumor tissue samples, all of them were consistently detected and the variant allele frequencies (VAFs) of the mutations were almost identical between targeted NGS and dPCR. When we examined the KRAS mutations using the plasma cfDNA of the three CRC patients by dPCR, all three mutations were consistently identified. However, the VAFs were lower (range, 0.166% to 2.638%) than those obtained using the CRC tissue samples. In conclusion, we confirmed that the KRAS mutations identified from CRC tumor tissue samples were consistently detected in the plasma cfDNA of the three CRC patients by dPCR.

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

• Journal of Life Science
• /
• v.24 no.11
• /
• pp.1258-1267
• /
• 2014

Developing economic traits with a high growth rate, robustness, and disease resistance in livestock is an important challenge. RFLP and AFLP are the classical methods used to develop economic traits. Whole-genome-based economic traits have recently been detected with the advent of next-generation sequencing (NGS) technologies. However, NGS technologies are rather costly for use in studies, and RNA-seq, RAD-Seq, RRL, MSG, and GBS have been used to overcome the issue of high costs. In this study, recent NGS-based studies were reviewed, particularly those that focused on minimum costs and maximum effects. Then, we presented further prospects on how to apply for selection of high economic-trait livestock.

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