• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7221-7227
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• 2013

Background: Fascin, an actin-bundling protein forming actin bundles including filopodia and stress fibers, is overexpressed in multiple human epithelial cancers including esophageal squamous cell carcinoma (ESCC). Previously we conducted a microarray experiment to analyze fascin knockdown by RNAi in ESCC. Method: In this study, the differentially expressed genes from mRNA expression profilomg of fascin knockdown were analyzed by multiple bioinformatics methods for a comprehensive understanding of the role of fascin. Results: Gene Ontology enrichment found terms associated with cytoskeleton organization, including cell adhesion, actin filament binding and actin cytoskeleton, which might be related to fascin function. Except GO categories, the differentially expressed genes were annotated by 45 functional categories from the Functional Annotation Chart of DAVID. Subpathway analysis showed thirty-nine pathways were disturbed by the differentially expressed genes, providing more detailed information than traditional pathway enrichment analysis. Two subpathways derivated from regulation of the actin cytoskeleton were shown. Promoter analysis results indicated distinguishing sequence patterns and transcription factors in response to the co-expression of downregulated or upregulated differentially expressed genes. MNB1A, c-ETS, GATA2 and Prrx2 potentially regulate the transcription of the downregulated gene set, while Arnt-Ahr, ZNF42, Ubx and TCF11-MafG might co-regulate the upregulated genes. Conclusions: This multiple bioinformatic analysis helps provide a comprehensive understanding of the roles of fascin after its knockdown in ESCC.

• Genomics & Informatics
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• v.20 no.3
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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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• v.14 no.11
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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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• v.45 no.5
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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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• v.2 no.4
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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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• v.8 no.1
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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.

• Journal of Life Science
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• v.19 no.8
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• pp.1159-1163
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• 2009

It has been postulated that endoplasmic (ER) stress is involved in the development of several diseases. However, the detailed molecular mechanisms have not been fully understood. Therefore, we characterized a genetic network of genes induced by ER stress using cDNA microarray and gene set expression coherence analysis (GSECA), and identified gene function as well as several transcription regulators associated with ER stress. We analyzed time-dependent gene expression profiles in thapsigargin-treated Sk-Hep1 using an oligonucleotide expression chip, and then selected functional gene sets with significantly high expression coherence which was processed into functional clusters according to the expression similarities. The functions related to sugar binding, lysosome, ribosomal protein, ER lumen, and ER to golgi transport increased, whereas the functions with mRNA processing, DNA replication, DNA repair, cell cycle, electron transport chain and helicase activity decreased. Furthermore, functional clusters were investigated for the enrichment of regulatory motifs using GSECA, and several transcriptional regulators associated with regulation of ER-induced gene expression were found.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1795-1801
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• 2018

Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.

• Journal of Veterinary Science
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• v.24 no.1
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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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• v.32 no.4
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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.