• Genomics & Informatics
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• 제20권3호
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.

• Asian Pacific Journal of Cancer Prevention
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• 제14권11호
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• pp.6347-6350
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• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Molecules and Cells
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• 제45권5호
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• pp.306-316
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• 2022

Chronic stress contributes to the risk of developing depression; the habenula, a nucleus in epithalamus, is associated with many neuropsychiatric disorders. Using genome-wide gene expression analysis, we analyzed the transcriptome of the habenula in rats exposed to chronic restraint stress for 14 days. We identified 379 differentially expressed genes (DEGs) that were affected by chronic stress. These genes were enriched in neuroactive ligand-receptor interaction, the cAMP (cyclic adenosine monophosphate) signaling pathway, circadian entrainment, and synaptic signaling from the Kyoto Encyclopedia of Genes and Genomes pathway analysis and responded to corticosteroids, positive regulation of lipid transport, anterograde trans-synaptic signaling, and chemical synapse transmission from the Gene Ontology analysis. Based on protein-protein interaction network analysis of the DEGs, we identified neuroactive ligand-receptor interactions, circadian entrainment, and cholinergic synapse-related subclusters. Additionally, cell type and habenular regional expression of DEGs, evaluated using a recently published single-cell RNA sequencing study (GSE137478), strongly suggest that DEGs related to neuroactive ligand-receptor interaction and trans-synaptic signaling are highly enriched in medial habenular neurons. Taken together, our findings provide a valuable set of molecular targets that may play important roles in mediating the habenular response to stress and the onset of chronic stress-induced depressive behaviors.

• Molecular & Cellular Toxicology
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• 제2권4호
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• pp.273-278
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• 2006

95 squamous cell lung carcinoma samples (normal tissue: 40 samples, tumor: 55 samples) were analyzed with 8 K cDNA microarray. 1-way ANOVA test was employed to select differentially expressed genes in tumor with FDR<0.01. Among the selected 1,655 genes, final 212 genes were chosen according to the expression fold change and used for following analysis. The expression of up-regulated 64 genes was verified with Reverse Transcription PCR and 10 genes were identified as candidates for SCC markers. In our opinion, those candidates can be exploited as diagnostic or therapeutic purposes. Gene Ontology (GO) based analysis was performed using those 212 genes, and following categories were revealed as significant biological processes: Immune response (GO: 0006955), antigen processing (GO: 0030333), inflammatory response (GO: 0006954), Cell adhesion (GO: 0007155), and Epidermis differentiation (GO: 0008544). Gene set enrichment analysis (GSEA) also carried out on overall gene expression profile with 522 functional gene sets. Glycolysis, cell cycle, K-ras and amino acid biosynthesis related gene sets were most distinguished. These results are consistent with the known characteristics of SCC and may be interconnected to rapid cell proliferation. However, the unexpected results from ERK activation in squamous cell carcinoma gripped our attention, and further studies are under progress.

• Genomics & Informatics
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• 제8권1호
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• pp.28-33
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• 2010

Increased exposure of human to RF fields has raised concerns for its potential adverse effects on our health. To address the biological effects of RF radiation, we used genome wide gene expression as the indicator. We exposed normal WI-38 human fibroblast cells to 1763 MHz mobile phone RF radiation at a specific absorption rate (SAR) of 60 W/kg with an operating cooling system for 24 h. There were no alterations in cell numbers or morphology after RF exposure. Through microarray analysis, we identified no differentially expressed genes (DEGs) at the 0.05 significance level after controlling for multiple testing errors with the Benjaminiochberg false discovery rate (BH FDR) method. Meanwhile, 82 genes were differentially expressed between RF-exposed cells and controls when the significance level was set at 0.01 without correction for multiple comparisons. We found that 24 genes (0.08% of the total genes examined) were changed by more than 1.5-fold on RF exposure. However, significant enrichment of any gene set or pathway was not observed from the functional annotation analysis. From these results, we did not find any evidence that non-thermal RF radiation at a 60-W/kg SAR significantly affects cell proliferation or gene expression in WI-38 cells.

• 생명과학회지
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• 제19권8호
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• pp.1159-1163
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• 2009

ER stress에 관련된 유전자의 기능변화와 전사조절인자 분석하기 위해 ER stress를 유도한 간세포에서 expression microarray로 유전자 발현을 확보한 후 GSECA로 분석하였다. ER stress가 유도되면, ER에 주어지는 과도한 부하를 감소시키는 기능들이 증가하는 반면, ER stress가 더 증가함에 따라 ATP 생성이나 DNA repair, 더 나아가 세포분열의 기능이 감소하는 등 세포가 damage을 받음을 알 수 있었다. ER stress에 관련된 전사조절인자로는 FOX04, AP-1, FOX03, HNF4, IRF-1, GATA 등의 전사조절인자들이 ER stress에 의해 발현이 증가하는 유전자들의 promoter에 공통적으로 존재하였으며, E2F, Nrf-1, Elk-1, YY1, CREB, MTF-1, STAT-1, ATF 등의 전사인자들이 발현이 감소하는 유전자들의 promoter에서 공통적으로 존재하여, 이들의 전사인자들이 ER stress에 의한 유전자의 발현조절에 중요한 역할을 하는 전사조절인자임을 알 수 있었다.

• 디지털콘텐츠학회 논문지
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• 제19권9호
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• pp.1795-1801
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• 2018

질환의 원인을 규명하기 위해 전장유전체 연관분석 (GWAS; Genome-Wide Association Study) 연구가 활발히 진행되고 유전체 레벨의 단일염기다형성 (SNP; Single-nucleotide polymorphism)이 많이 밝혀지고 있다. 그러나 단일염기다형성의 연관분석을 통해 질환이 발병하는 생물학적 메카니즘을 이해하기 어렵기 때문에 유전자, 생물학적 패스웨이 및 질환 등의 연관성 분석이 이전보다 더욱 중요하다. 본 논문에서는 단일염기다형성과 관련된 유전자와 패스웨이, 질환 정보를 검색하여 통합 분석하는 서비스를 제공하는 PRaDA 웹 시스템을 제안하였다. PRaDA는 사용자로부터 입력받은 유의한 몇몇의 단일염기다형성들과 관련된 유전자 및 패스웨이 뿐만 아니라, 유의하지 않은 다수의 단일염기다형성 집합의 간접적인 영향을 파악하기 위해 기능적으로 근접한 패스웨이를 검색하고 통계적 분석을 실행한다. 사용자들은 PRaDA가 제공하는 통합된 정보를 통해 질병의 전반적인 이해를 할 수 있다.

• Journal of Veterinary Science
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• 제24권1호
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• pp.13.1-13.11
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• 2023

Background: Highly pathogenic avian influenza viruses (HPAIVs) is an extremely contagious and high mortality rates in chickens resulting in substantial economic impact on the poultry sector. Therefore, it is necessary to elucidate the pathogenic mechanism of HPAIV for infection control. Objective: Gene set enrichment analysis (GSEA) can effectively avoid the limitations of subjective screening for differential gene expression. Therefore, we performed GSEA to compare HPAI-infected resistant and susceptible Ri chicken lines. Methods: The Ri chickens Mx(A)/BF2(B21) were chosen as resistant, and the chickens Mx(G)/BF2(B13) were selected as susceptible by genotyping the Mx and BF2 genes. The tracheal tissues of HPAIV H5N1 infected chickens were collected for RNA sequencing followed by GSEA analysis to define gene subsets to elucidate the sequencing results. Results: We identified four differentially expressed pathways, which were immune-related pathways with a total of 78 genes. The expression levels of cytokines (IL-1β, IL-6, IL-12), chemokines (CCL4 and CCL5), type interferons and their receptors (IFN-β, IFNAR1, IFNAR2, and IFNGR1), Jak-STAT signaling pathway genes (STAT1, STAT2, and JAK1), MHC class I and II and their co-stimulatory molecules (CD80, CD86, CD40, DMB2, BLB2, and B2M), and interferon stimulated genes (EIF2AK2 and EIF2AK1) in resistant chickens were higher than those in susceptible chickens. Conclusions: Resistant Ri chickens exhibit a stronger antiviral response to HPAIV H5N1 compared with susceptible chickens. Our findings provide insights into the immune responses of genetically disparate chickens against HPAIV.

• Asian-Australasian Journal of Animal Sciences
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• 제32권4호
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• 한국컴퓨터정보학회논문지
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• 제15권12호
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• pp.197-207
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• 2010

대용량(High-throughput) 형태로 얻어진 cDNA 마이크로어레이 데이터에 다양한 데이터 마이닝 기법을 적용하면 서로 다른 조직에서 추출한 유전자의 발현정도를 비교할 수 있고 정상세포와 암세포에서 발현량의 차이를 보이는 DEG(Differently Expression Gene) 유전자를 추출할 수 있다. 이들을 이용하여 병을 진단할 수 있을 뿐만 아니라, 암의 진행 단계(Cancer Stage)에 따른 치료 방법을 결정할 수 있다. 마이크로어레이를 기반으로 한 대부분의 암 분류자는 기계학습 기법을 이용하여 암 관련 유전자를 추출하여, 이들 유전자를 총체적으로 이용하여 독립 샘플의 클래스(암, 정상)를 판정한다. 하지만 유전자의 발현량의 차이뿐만 아니라 유전자와 유전자의 상관관계의 변화가 질병 진단에 활용될 수 있다. 대부분의 질병은 단독 유전자의 변이에 의한 것이 아니라 유전자의 모듈로 이루어진 유전자조절네트워크의 변이에 의한 것이기 때문이다. 본 논문에서는 조건에 따라 특이적 관계를 나타내는 유전자 쌍을 식별하여, 이들 유전자 쌍을 이용한 유전자 분류 모듈을 생성한다. 분류 모듈을 이용한 암 분류 방법이 기존의 암 분류 방법보다 높은 정확도로 암과정상 샘플을 분류함을 보여주고 있다. 분류 모듈을 구성하는 유전자의 수가 상대적으로 적으므로 임상키트로의 개발도 고려할 수 있다. 향후 분류 모듈에 속하는 유전자의 기능적 검증을, GO(Gene Ontology)를 활용함으로서, 밝혀지지 않은 새로운 암 관련 유전자를 식별하고, 분류 모듈을 확대하여 암 특이적 유전자조절네트워크 구성에 활용할 계획이다.