• Genomics & Informatics
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• v.20 no.1
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• pp.2.1-2.11
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• 2022

The method of single-cell RNA sequencing has been rapidly developed, and numerous experiments have been conducted over the past decade. Their results allow us to recognize various subpopulations and rare cell states in tissues, tumors, and immune systems that are previously unidentified, and guide us to understand fundamental biological processes that determine cell identity based on single-cell gene expression profiles. However, it is still challenging to understand the principle of comprehensive gene regulation that determines the cell fate only with transcriptome, a consequential output of the gene expression program. To elucidate the mechanisms related to the origin and maintenance of comprehensive single-cell transcriptome, we require a corresponding single-cell epigenome, which is a differentiated information of each cell with an identical genome. This review deals with the current development of single-cell epigenomic library construction methods, including multi-omics tools with crucial factors and additional requirements in the future focusing on DNA methylation, chromatin accessibility, and histone post-translational modifications. The study of cellular differentiation and the disease occurrence at a single-cell level has taken the first step with single-cell transcriptome and is now taking the next step with single-cell epigenome.

• BMB Reports
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• v.55 no.9
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• pp.417-428
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• 2022

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network-based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound-target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in high-throughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data.

• 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.

• IMMUNE NETWORK
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• v.23 no.1
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• pp.8.1-8.13
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• 2023

CD8⁺ T cells are activated by TCRs that recognize specific cognate Ags, while NK-cell activation is regulated by a balance between signals from germline-encoded activating and inhibitory NK receptors. Through these different processes of Ag recognition, CD8⁺ T cells and NK cells play distinct roles as adaptive and innate immune cells, respectively. However, some human CD8⁺ T cells have been found to express activating or inhibitory NK receptors. CD8⁺ T-cell populations expressing NK receptors straddle the innate-adaptive boundary with their innate-like features. Recent breakthrough technical advances in multi-omics analysis have enabled elucidation of the unique immunologic characteristics of these populations. However, studies have not yet fully clarified the heterogeneity and immunological characteristics of each CD8⁺ T-cell population expressing NK receptors. Here we aimed to review the current knowledge of various CD8⁺ T-cell populations expressing NK receptors, and to pave the way for delineating the landscape and identifying the various roles of these T-cell populations.

• Genomics & Informatics
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• v.18 no.1
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• pp.8.1-8.10
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• 2020

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.

• Biomolecules & Therapeutics
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• v.28 no.3
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• pp.282-291
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• 2020

Inhaled solvents such as toluene are of particular concern due to their abuse potential that is easily exposed to the environment. The inhalation of toluene causes various behavioral problems, but, the effect of short-term exposure of toluene on changes in emotional behaviors over time after exposure and the accompanying pathological characteristics have not been fully identified. Here, we evaluated the behavioral and neurochemical changes observed over time in mice that inhaled toluene. The mice were exposed to toluene for 30 min at a concentration of either 500 or 2,000 ppm. Toluene did not cause social or motor dysfunction in mice. However, increased anxiety-like behavior was detected in the short-term after exposure, and depression-like behavior appeared as delayed effects. The amount of striatal dopamine metabolites was significantly decreased by toluene, which continued to be seen for up to almost two weeks after inhalation. Additionally, an upregulation of serotonin 1A (5-HT_1A) receptor in the hippocampus and the substantia nigra, as well as reduced immunoreactivity of neurogenesis markers in the dentate gyrus, was observed in the mice after two weeks. These results suggest that toluene inhalation, even single exposure, mimics early anxiety-and delayed depression-like emotional disturbances, underpinned by pathological changes in the brain.

• Research in Plant Disease
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• v.21 no.3
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• pp.161-179
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• 2015

Plant have developed sophisticated defence mechanisms against microbial pathogens. The recent accumulated information allow us to understand the nature of plant immune responses followed by recognition of microbial factors/determinants through cutting-edge genomics and multi-omics techniques. However, the practical approaches to sustain plant health using enhancement of plant immunity is yet to be fully appreciated. Here, we overviewed the general concept and representative examples on the plant immunity. The fungal, bacterial, and viral determinants that was previously reported as the triggers of plant immune responses are introduced and described as the potential protocol of biological control. Specifically, the role of chitin, glucan, lipopolysaccharides/extracellular polysaccharides, microbe/pathogen-associated molecular pattern, antibiotics, mimic-phytohormones, N-acyl homoserine lactone, harpin, vitamins, and volatile organic compounds are considered. We hope that this review stimulates scientific community and farmers to broaden their knowledge on the microbial determinant-based biological control and to apply the technology on the integrated pest management program.

• BMB Reports
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• v.53 no.6
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• pp.299-310
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• 2020

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.

• Molecules and Cells
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• v.42 no.4
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• pp.333-344
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• 2019

Various genetic and environmental factors are known to be associated with chronic obstructive pulmonary disease (COPD). We identified COPD-related differentially expressed genes (DEGs) using 189 samples accompanying either adenocarcinoma (AC) or squamous cell carcinoma (SC), comprising 91 normal and 98 COPD samples. DEGs were obtained from the intersection of two DEG sets separately identified for AC and SC to exclude the influence of different cancer backgrounds co-occurring with COPD. We also measured patient samples named group 'I', which were unable to be determined as normal or COPD based on alterations in gene expression. The Gene Ontology (GO) analysis revealed significant alterations in the expression of genes categorized with the 'cell adhesion', 'inflammatory response', and 'mitochondrial functions', i.e., well-known functions related to COPD, in samples from patients with COPD. Multi-omics data were subsequently integrated to decipher the upstream regulatory changes linked to the gene expression alterations in COPD. COPD-associated expression quantitative trait loci (eQTLs) were located at the upstream regulatory regions of 96 DEGs. Additionally, 45 previously identified COPD-related miRNAs were predicted to target 66 of the DEGs. The eQTLs and miRNAs might affect the expression of 'respiratory electron transport chain' genes and 'cell proliferation' genes, respectively, while both eQTLs and miRNAs might affect the expression of 'apoptosis' genes. We think that our present study will contribute to our understanding of the molecular etiology of COPD accompanying lung cancer.

• BMB Reports
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• v.54 no.10
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• pp.497-504
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• 2021

EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2- BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC.