• The Korean Journal of Physiology and Pharmacology
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• v.28 no.5
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• pp.403-411
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• 2024

The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.

• Korean Journal of Plant Taxonomy
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• v.48 no.3
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• pp.195-200
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• 2018

Genetic assessments of rare and endangered species are among the first steps necessary to establish the proper management of natural populations. Transcriptome-derived single-sequence repeat markers were developed for the Korean endangered species Astilboides tabularis (Saxifragaceae) to assess its genetic diversity. A total of 96 candidate microsatellite loci were isolated based on transcriptome data using Illumina pair end sequencing. Of these, 26 were polymorphic, with one to five alleles per locus in 60 individuals from three populations of A. tabularis. The observed and expected heterozygosity per locus ranged from 0.000 to 0.950 and from 0.000 to 0.741, respectively. These polymorphic transcriptome-derived simple sequence repeat markers would be invaluable for future studies of population genetics and for ecological conservation of the endangered species A. tabularis.

• BMB Reports
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• v.55 no.3
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• pp.113-124
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• 2022

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

• Genomics & Informatics
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• v.19 no.1
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• pp.2.1-2.10
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• 2021

BRAF inhibitors (e.g., vemurafenib) are widely used to treat metastatic melanoma with the BRAF V600E mutation. The initial response is often dramatic, but treatment resistance leads to disease progression in the majority of cases. Although secondary mutations in the mitogen-activated protein kinase signaling pathway are known to be responsible for this phenomenon, the molecular mechanisms governing acquired resistance are not known in more than half of patients. Here we report a genome- and transcriptome-wide study investigating the molecular mechanisms of acquired resistance to BRAF inhibitors. A microfluidic chip with a concentration gradient of vemurafenib was utilized to rapidly obtain therapy-resistant clones from two melanoma cell lines with the BRAF V600E mutation (A375 and SK-MEL-28). Exome and transcriptome data were produced from 13 resistant clones and analyzed to identify secondary mutations and gene expression changes. Various mechanisms, including phenotype switching and metabolic reprogramming, have been determined to contribute to resistance development differently for each clone. The roles of microphthalmia-associated transcription factor, the master transcription factor in melanocyte differentiation/dedifferentiation, were highlighted in terms of phenotype switching. Our study provides an omics-based comprehensive overview of the molecular mechanisms governing acquired resistance to BRAF inhibitor therapy.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.253-253
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• 2022

Codonopsis lanceolata (C. lanceolata) has been widely used in East Asia as a traditional medicine to treat various diseases such as bronchitis, convulsions, cough, obesity, and hepatitis. C. lanceolata belonging to Campanulaceae contains bioactive compounds such as polyphenols, saponins, and steroids. However, despite the pharmacological significance of C. lanceolata, the genetic information of this plant is limited and there are few studies of its transcriptome. In this study, we constructed a unigene set of C. lanceolata using Pac-Bio sequencing. Furthermore, the reads generated from Pac-bio and Illumina sequencing were mixed and assembled using rnaSPAdes. All genes involved in the triterpenoid pathway, a major bioactive compounds of C. lanceolata, were searched from the two unigene sets and the expression profiles of these genes were analyzed. The results showed that lupeol, beta-amyrin, and dammarenediol synthesis genes were activated in the leaves and roots of C. lanceolata. In particular, the expression of genes related to lupeol synthesis was relatively high, suggesting that the main triterpenoid of C. lanceolata is lupeol. Transcriptome studies related to lupeol synthesis in C. lanceolata have been rarely reported. Lupeol has been reported to have pharmacological effects such as anti-inflammatory, anti-cancer, and anti-bacterial. This study suggests the importance of C. lanceolata as a lupeol producing plant.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.167-172
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• 2012

In biology the advent of the high-throughput technology for sequencing, probing, or screening has produced huge volume of data which could not be manually handled. Biologists have resorted to software tools in order to effectively handle them. This paper introduces a bioinformatics tool to help biologists find potentially interesting pathway maps from a transcriptome data set in which the expression levels of genes are described for both case and control samples. The tool accepts a transcriptome data set, and then selects and categorizes some of genes into four classes using a fuzzy filtering technique where classes are defined by membership functions. It collects and edits the pathway maps related to those selected genes without analyst' intervention. It invokes a sequence of web service functions from KEGG, which an online pathway database system, in order to retrieve related information, locate pathway maps, and manipulate them. It maintains all retrieved pathway maps in a local database and presents them to the analysts with graphical user interface. The tool has been successfully used in identifying target genes for further analysis in transcriptome study of human cytomegalovirous. The tool is very helpful in that it can considerably save analysts' time and efforts by collecting and presenting the pathway maps that contain some interesting genes, once a transcriptome data set is just given.

• The Plant Pathology Journal
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• v.33 no.4
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• pp.362-369
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• 2017

White root rot disease, caused by the pathogen Rosellinia necatrix, is one of the world's most devastating plant fungal diseases and affects several commercially important species of fruit trees and crops. Recent global outbreaks of R. necatrix and advances in molecular techniques have both increased interest in this pathogen. However, the lack of information regarding the genomic structure and transcriptome of R. necatrix has been a barrier to the progress of functional genomic research and the control of this harmful pathogen. Here, we identified 10,616 novel full-length transcripts from the filamentous hyphal tissue of R. necatrix (KACC 40445 strain) using PacBio single-molecule sequencing technology. After annotation of the unigene sets, we selected 14 cell cycle-related genes, which are likely either positively or negatively involved in hyphal growth by cell cycle control. The expression of the selected genes was further compared between two strains that displayed different growth rates on nutritional media. Furthermore, we predicted pathogen-related effector genes and cell wall-degrading enzymes from the annotated gene sets. These results provide the most comprehensive transcriptomal resources for R. necatrix, and could facilitate functional genomics and further analyses of this important phytopathogen.

• Development and Reproduction
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• v.27 no.1
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• pp.9-24
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• 2023

The advancement in high-throughput sequencing (HTS) technology has revolutionized the field of biology, including genomics, epigenomics, transcriptomics, and metagenomics. This technology has become a crucial tool in many areas of research, allowing scientists to generate vast amounts of genetic data at a much faster pace than traditional methods. With this increased speed and scale of data generation, researchers can now address critical questions and gain new insights into the inner workings of living organisms, as well as the underlying causes of various diseases. Although the first HTS technology have been introduced about two decades ago, it can still be challenging for those new to the field to understand and use effectively. This review aims to provide a comprehensive overview of commonly used HTS technologies these days and their applications in terms of genome sequencing, transcriptome, DNA methylation, DNA-protein interaction, chromatin accessibility, three-dimensional genome organization, and microbiome.

• Journal of Animal Science and Technology
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• v.58 no.4
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• pp.17.1-17.7
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• 2016

Background: The Sapsaree (Canis familiaris) is a Korean native dog that is very friendly, protective, and loyal to its owner, and is registered as a natural monument in Korea (number: 368). To investigate large-scale gene expression profiles and identify the genes related to exercise-induced stress in the Sapsaree, we performed whole-transcriptome RNA sequencing and analyzed gene expression patterns before and after exercise performance. Results: We identified 525 differentially expressed genes in ten dogs before and after exercise. Gene Ontology classification and KEGG pathway analysis revealed that the genes were mainly involved in metabolic processes, such as programmed cell death, protein metabolic process, phosphatidylinositol signaling system, and cation binding in cytoplasm. The ten Sapsarees could be divided into two groups based on the gene expression patterns before and after exercise. The two groups were significantly different in terms of their basic body type ($p{\leq}0.05$). Seven representative genes with significantly different expression patterns before and after exercise between the two groups were chosen and characterized. Conclusions: Body type had a significant effect on the patterns of differential gene expression induced by exercise. Whole-transcriptome sequencing is a useful method for investigating the biological characteristics of the Sapsaree and the large-scale genomic differences of canines in general.

• BMB Reports
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• v.48 no.7
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• pp.388-394
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• 2015

The brain is an organ that consists of various cell types. As our knowledge of the structure and function of the brain progresses, cell type-specific research is gaining importance. Together with advances in sequencing technology and bioinformatics, cell type-specific transcriptome studies are providing important insights into brain cell function. In this review, we discuss 3 different cell type-specific transcriptome analyses i.e., Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP)/RiboTag, and single cell RNA-Seq, that are widely used in the field of neuroscience. [BMB Reports 2015; 48(7): 388-394]