• Proceedings of the Botanical Society of Korea Conference
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• 1985.08b
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• pp.73-81
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• 1985

We have previously isolated OsMADS4 gene that is a member of the class B MADS box genes from rice. In this study, another member of the class B MADS box genes was isolated from rice flower by the yeast two-hybrid screening method using OsMADS4 as bait. RNA blot analyses revealed that the clone, OsMADS16, was expressed in the second and third whorls, whereas the OsMADS4 transcripts were present in the second, third, and fourth whorls. These expression patterns of the OsMADS16 and OsMADS4 genes are very similar with those of AP3 and PI, the class B genes of Arabidopsis, respectively. In the yeast two-hybrid system, OsMADS4 interacted only with OsMADS16 among several rice MADS genes investigated, suggesting that OsMADS4 and OsMADS16 function as a heterodimer in specifying sepal and petal identities. We have also isolated OsMADS6 gene using OsMADS1 as a probe. Both are members of the AGL2 MADS family. Various MADS genes that encode for protein-protein interaction partners of the OsMADS6 protein were isolated by the yeast two-hybrid screening method. A majority of these genes belong to the AGL2 family. Sequence Homology, expression pattern, and ectopic expression phenotypes indicated that one of the interaction partners, OsMADS14, appears to be homologous to API, the class A MADS gene of Arabidopsis.

• Journal of Animal Science and Technology
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• v.60 no.6
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• pp.11.1-11.7
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• 2018

After pubertal, cohort of small antral follicles enters to gonadotrophin-sensitive development, called recruited follicles. This study was aimed to identify candidate genes in follicular cyclic recruitment via analysis of protein-protein interaction (PPI) network. Differentially expressed genes (DEGs) in ovine granulosa cells of small antral follicles between follicular and luteal phases were accumulated among gene/protein symbols of the Ensembl annotation. Following directed graphs, PTPN6 and FYN have the highest indegree and outdegree, respectively. Since, these hubs being up-regulated in ovine granulosa cells of small antral follicles during the follicular phase, it represents an accumulation of blood immune cells in follicular phase in comparison with luteal phase. By contrast, the up-regulated hubs in the luteal phase including CDK1, INSRR and TOP2A which stimulated DNA replication and proliferation of granulosa cells, they known as candidate genes of the cyclic recruitment.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2561-2567
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• 2015

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.693-703
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• 2010

Diseases of human or economical traits of cattles are occured by interaction of genes. We introduce expanded multifactor dimensionality reduction(E-MDR), dummy multifactor dimensionality reduction(D-MDR) and SNPHarvester which are developed to find interaction of genes. We will select interaction of outstanding gene combinations and select final best genotype groups.

• The Plant Pathology Journal
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• v.35 no.3
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• pp.257-273
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• 2019

Tomato (Solanum lycopersicum) is one of the most widely grown and economically important vegetable crops in the world. Tomato chlorosis virus (ToCV) is one of the recently emerged viruses of tomato distributed worldwide. ToCV-tomato interaction was investigated at the molecular level for determining changes in the expression of tomato genes in response to ToCV infection in this study. A cDNA library enriched with genes induced in response to ToCV infection were constructed and 240 cDNAs were sequenced from this library. The macroarray analysis of 108 cDNAs revealed that the expression of 92 non-redundant tomato genes was induced by 1.5-fold or greater in response to ToCV infection. The majority of ToCV-induced genes identified in this study were associated with a variety of cellular functions including transcription, defense and defense signaling, metabolism, energy, transport facilitation, protein synthesis and fate and cellular biogenesis. Twenty ToCV-induced genes from different functional groups were selected and induction of 19 of these genes in response to ToCV infection was validated by RT-qPCR assay. Finally, the expression of 6 selected genes was analyzed in different stages of ToCV infection from 0 to 45 dpi. While the expression of three of these genes was only induced by ToCV infection, others were induced both by ToCV infection and wounding. The result showed that ToCV induced the basic defense response and activated the defense signaling in tomato plants at different stages of the infection. Functions of these defense related genes and their potential roles in disease development and resistance to ToCV are also discussed.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.8
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• pp.4553-4557
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• 2013

Objective: The purpose of this study was to identify genes related to bladder cancer with samples from normal and disease cases by microarray chip. Methods: After downloading the gene expression profile GSE3167 from Gene Expression Omnibus database which includes 50 bladder samples, comprising 9 normal and 41 disease samples, differentially expressed genes were identified with packages in R language. The selected differentially expressed genes were further analyzed using bioinformatics methods. Firstly, molecular functions, biological processes and cell component analysis were researched by software Gestalt. Then, software String was used to search interaction relationships among differentially expressed genes, and hub genes of the network were selected. Finally, by using plugins of software Cytoscape, Mcode and Bingo, module analysis of hub-genes was performed. Results: A total of 221 genes were identified as differentially expressed by comparing normal and disease bladder samples, and a network as well as the hub gene C1QBP was obtained from the network. The C1QBP module had the closest relationship to production of molecular mediators involved in inflammatory responses. Conclusion: We obtained differentially expressed genes of bladder cancer by microarray, and both PRDX2 and YWHAZ in the module with hub gene C1QBP were most significantly related to production of molecular mediators involved in inflammatory responses. From knowledge of inflammatory responses and cancer, our results showed that, the hub gene and its module could induce inflammation in bladder cancer. These related genes are candidate bio-markers for bladder cancer diagnosis and might be helpful in designing novel therapies.

• 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.

• The Plant Pathology Journal
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• v.30 no.4
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• pp.425-431
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• 2014

Leaf scald caused by the infection of Rhynchosporium secalis, is a worldwide crop disease resulting in significant loss of barley yield. In this study, a systematic sequencing of expressed sequence tags (ESTs) was chosen to obtain a global picture of the assembly of genes involved in pathogenesis. To identify a large number of plant ESTs, which are induced at different time points, an amplified fragment length polymorphism (AFLP) display of complementary DNA (cDNA) was utilized. Transcriptional changes of 140 ESTs were observed, of which 19 have no previously described function. Functional annotation of the transcripts revealed a variety of infection-induced host genes encoding classical pathogenesis-related (PR) or genes that play a role in the signal transduction pathway. The expression analyses by a semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) revealed that Rar1 and Rpg4 are defense inducible genes, and were consistent with the cDNA-AFLP data in their expression patterns. Hence, the here presented transcriptomic approach provides novel global catalogue of genes not currently represented in the EST databases.

• 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.

• Journal of Environmental Health Sciences
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• v.36 no.1
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• pp.1-13
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• 2010

Evidences supporting gene-environment interaction are accumulating in terms of environmental exposure including lifestyle factors and related genetic variants. One form of defense mechanism against cancer development involves a series of genes whose role is to metabolize (activation/detoxification) and excrete potentially toxic compounds and to repair subtle mistakes in DNA. The purpose of this article is to provide a brief review of the notion of gene-environment interaction, environmental/occupational carcinogens and related cancers, and previous studies of gene-environment interaction on cancers caused by exposure to carcinogenesis. With a number of studies on the interaction between lifestyle factors (e.g., smoking and diet) and genetic polymorphisms in genes involved in xenobiotic metabolism and DNA repair excluded, only several studies have been conducted on the interactive effects between polymorphisms of CYPs, GSTs, ERCCs, XRCCs and environmental/occupational carcinogens such as vinyl chloride, benzo[a]pyrene, and chloroform on carcinogenesis or genotoxicity. Future studies may need to be conducted with sufficient number of subjects and based on occupational cohorts to provide useful information in terms of advanced risk assessment and regulation of exposure level.