• Genomics & Informatics
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• v.21 no.4
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• pp.45.1-45.11
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• 2023

Nonalcoholic fatty liver disease (NAFLD) is a common type of chronic liver disease, with severity levels ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH). The extent of liver fibrosis indicates the severity of NASH and the risk of liver cancer. However, the mechanism underlying NASH development, which is important for early screening and intervention, remains unclear. Weighted gene co-expression network analysis (WGCNA) is a useful method for identifying hub genes and screening specific targets for diseases. In this study, we utilized an mRNA dataset of the liver tissues of patients with NASH and conducted WGCNA for various stages of liver fibrosis. Subsequently, we employed two additional mRNA datasets for validation purposes. Gene set enrichment analysis (GSEA) was conducted to analyze gene function enrichment. Through WGCNA and subsequent analyses, complemented by validation using two additional datasets, we identified five genes (BICC1, C7, EFEMP1, LUM, and STMN2) as hub genes. GSEA analysis indicated that gene sets associated with liver metabolism and cholesterol homeostasis were uniformly downregulated. BICC1, C7, EFEMP1, LUM, and STMN2 were identified as hub genes of NASH, and were all related to liver metabolism, NAFLD, NASH, and related diseases. These hub genes might serve as potential targets for the early screening and treatment of NASH.

• Animal Bioscience
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• v.35 no.6
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• pp.814-825
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• 2022

Objective: This study was conducted to identify the functional long non-coding RNAs (lncRNAs) for swine lactation by RNA-seq data of mammary gland. Methods: According to the RNA-seq data of swine mammary gland, we screened lncRNAs, performed differential expression analysis, and confirmed the functional lncRNAs for swine lactation by validation of genome wide association study (GWAS) signals, functional annotation and weighted gene co-expression network analysis (WGCNA). Results: We totally identified 286 differentially expressed (DE) lncRNAs in mammary gland at different stages from 14 days prior to (-) parturition to day 1 after (+) parturition, and the expressions of most of lncRNAs were strongly changed from day -2 to day +1. Further, the GWAS signals of sow milk ability trait were significantly enriched in DE lncRNAs. Functional annotation revealed that these DE lncRNAs were mainly involved in mammary gland and lactation developing, milk composition metabolism and colostrum function. By performing weighted WGCNA, we identified 7 out of 12 lncRNA-mRNA modules that were highly associated with the mammary gland at day -14, day -2, and day +1, in which, 35 lncRNAs and 319 mRNAs were involved. Conclusion: This study suggested that 18 lncRNAs and their 20 target genes were promising candidates for swine parturition and colostrum occurrence processes. Our research provided new insights into lncRNA profiles and their regulating mechanisms from colostrogenesis to lactogenesis in swine.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4251-4256
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• 2015

Background: Exposure to cigarette may affect human health and increase risk of a wide range of diseases including pulmonary diseases, such as chronic obstructive pulmonary disease (COPD), asthma, lung fibrosis and lung cancer. However, the molecular mechanisms of pathogenesis induced by cigarettes still remain obscure even with extensive studies. With systemic view, we attempted to identify the specific gene modules that might relate to injury caused by cigarette smoke and identify hub genes for potential therapeutic targets or biomarkers from specific gene modules. Materials and Methods: The dataset GSE18344 was downloaded from the Gene Expression Omnibus (GEO) and divided into mouse cigarette smoke exposure and control groups. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to construct a gene co-expression network for each group and detected specific gene modules of cigarette smoke exposure by comparison. Results: A total of ten specific gene modules were identified only in the cigarette smoke exposure group but not in the control group. Seven hub genes were identified as well, including Fip1l1, Anp32a, Acsl4, Evl, Sdc1, Arap3 and Cd52. Conclusions: Specific gene modules may provide better understanding of molecular mechanisms, and hub genes are potential candidates of therapeutic targets that may possible improve development of novel treatment approaches.

• Animal Bioscience
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• v.37 no.7
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• pp.1141-1155
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• 2024

Objective: RNA epigenetic modifications play an important role in regulating immune response of mammals. Bovine mastitis induced by Staphylococcus aureus (S. aureus) is a threat to the health of dairy cattle. There are numerous RNA modifications, and how these modification-associated enzymes systematically coordinate their immunomodulatory effects during bovine mastitis is not well reported. Therefore, the role of common RNA modification-related genes (RMRGs) in bovine S. aureus mastitis was investigated in this study. Methods: In total, 80 RMRGs were selected for this study. Four public RNA-seq data sets about bovine S. aureus mastitis were collected and one additional RNA-seq data set was generated by this study. Firstly, quantitative trait locus (QTL) database, transcriptome-wide association studies (TWAS) database and differential expression analyses were employed to characterize the potential functions of selected enzyme genes in bovine S. aureus mastitis. Correlation analysis and weighted gene co-expression network analysis (WGCNA) were used to further investigate the relationships of RMRGs from different types at the mRNA expression level. Interference experiments targeting the m⁶ A demethylase FTO and utilizing public MeRIP-seq dataset from bovine Mac-T cells were used to investigate the potential interaction mechanisms among various RNA modifications. Results: Bovine QTL and TWAS database in cattle revealed associations between RMRGs and immune-related complex traits. S. aureus challenged and control groups were effectively distinguished by principal component analysis based on the expression of selected RMRGs. WGCNA and correlation analysis identified modules grouping different RMRGs, with highly correlated mRNA expression. The m⁶ A modification gene FTO showed significant effects on the expression of m⁶ A and other RMRGs (such as NSUN2, CPSF2, and METTLE), indicating complex co-expression relationships among different RNA modifications in the regulation of bovine S. aureus mastitis. Conclusion: RNA epigenetic modification genes play important immunoregulatory roles in bovine S. aureus mastitis, and there are extensive interactions of mRNA expression among different RMRGs. It is necessary to investigate the interactions between RNA modification genes regulating complex traits in the future.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.1
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• pp.31-43
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• 2017

Together with radiotherapy, chemotherapy using cytotoxic agents is one of the most common therapies in cancer. Metabolic changes in cancer cells are drawing much attention recently, but the metabolic alterations by anticancer agents have not been much studied. Here, we investigated the effects of commonly used cytotoxic agents on lung normal cell MRC5 and lung cancer cell A549. We employed cis-plastin, doxorubicin, and 5-Fluorouracil and compared their effects on the viability and metabolism of the normal and cancer cell lines. We first established the concentration of the cytotoxic reagents that give differences in the viabilities of normal and cancer cell lines. In those conditions, the viability of A549 decreased significantly, whereas that of MRC5 remained unchanged. To study the metabolic alterations implicated in the viability differences, we obtained the metabolic profiles using $^1H$-NMR spectrometry. The $^1H$-NMR data showed that the metabolic changes of A549 cells are more remarkable than that of MRC5 cells and the effect of 5-FU on the A549 cells is the most distinct compared to other treatments. Heat map analysis showed that metabolic alterations under treatment of cytotoxic agents are totally different between normal and cancer cells. Multivariate analysis and weighted correlation network analysis (WGCNA) revealed a distinctive metabolite signature and hub metabolites. Two different analysis tools revealed that the changes of cell metabolism in response to cytotoxic agents were highly correlated with the Warburg effect and Reductive lipogenesis, two pathways having important effects on the cell survival. Taken together, our study addressed the correlation between the viability and metabolic profiles of MRC5 and A549 cells upon the treatment of cytotoxic anticancer agents.

• Parasites, Hosts and Diseases
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• v.58 no.5
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• pp.513-525
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• 2020

Clonorchis sinensis is a food-borne trematode that infects more than 15 million people. The liver fluke causes clonorchiasis and chronical cholangitis, and promotes cholangiocarcinoma. The underlying molecular pathogenesis occurring in the bile duct by the infection is little known. In this study, transcriptome profile in the bile ducts infected with C. sinensis were analyzed using microarray methods. Differentially expressed genes (DEGs) were 1,563 and 1,457 at 2 and 4 weeks after infection. Majority of the DEGs were temporally dysregulated at 2 weeks, but 519 DEGs showed monotonically changing expression patterns that formed seven distinct expression profiles. Protein-protein interaction (PPI) analysis of the DEG products revealed 5 sub-networks and 10 key hub proteins while weighted co-expression network analysis (WGCNA)-derived gene-gene interaction exhibited 16 co-expression modules and 13 key hub genes. The DEGs were significantly enriched in 16 Kyoto Encyclopedia of Genes and Genomes pathways, which were related to original systems, cellular process, environmental information processing, and human diseases. This study uncovered a global picture of gene expression profiles in the bile ducts infected with C. sinensis, and provided a set of potent predictive biomarkers for early diagnosis of clonorchiasis.

• Genomics & Informatics
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• v.21 no.3
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• pp.38.1-38.8
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• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• Journal of Life Science
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• v.30 no.1
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• pp.45-57
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• 2020

The prenatal period in livestock animals is crucial for meat production because net increase in the number of muscle fibers is finished before birth. However, there is no study on the growth and development mechanism of muscles in Hanwoo during this period. Therefore, to find candidate genes involved in muscle growth and development during this period in Hanwoo, mRNA expression data of longissimus in Hanwoo at 6 and 9 months post-conceptional age (MPA) were analyzed. We independently identified differentially expressed genes (DEGs) using DESeq2 and edgeR which are R software packages, and considered the overlaps of the results as final-DEGs to use in downstream analysis. The DEGs were classified into several modules using WGCNA then the modules' functions were analyzed to identify modules which involved in myogenesis and adipogenesis. Finally, the hub genes which had the highest WGCNA module membership among the top 10% genes of the STRING network maximal clique centrality were identified. 913(6 MPA specific DEGs) and 233(9 MPA specific DEGs) DEGs were figured out, and these were classified into five and two modules, respectively. Two of the identified modules'(one was in 6, and another was in 9 MPA specific modules) functions was found to be related to myogenesis and adipogenesis. One of the hub genes belonging to the 6 MPA specific module was axin1 (AXIN1) which is known as an inhibitor of Wnt signaling pathway, another was succinate-CoA ligase ADP-forming beta subunit (SUCLA2) which is known as a crucial component of citrate cycle.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.