• Asian-Australasian Journal of Animal Sciences
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• 제32권2호
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• pp.290-296
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• 2019

Objective: Pigs share many physiological, anatomical and genomic similarities with humans, which make them suitable models for biomedical researches. Understanding the genetic status of Yucatan miniature pigs (YMPs) and their association with human diseases will help to assess their potential as biomedical model animals. This study was performed to identify non-synonymous single nucleotide polymorphisms (nsSNPs) in selective sweep regions of the genome of YMPs and present the genetic nsSNP distributions that are potentially associated with disease occurrence in humans. Methods: nsSNPs in whole genome resequencing data from 12 YMPs were identified and annotated to predict their possible effects on protein function. Sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 analyses were used, and gene ontology (GO) network and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Results: The results showed that 8,462 genes, encompassing 72,067 nsSNPs were identified, and 118 nsSNPs in 46 genes were predicted as deleterious. GO network analysis classified 13 genes into 5 GO terms (p<0.05) that were associated with kidney development and metabolic processes. Seven genes encompassing nsSNPs were classified into the term associated with Alzheimer's disease by referencing the genetic association database. The KEGG pathway analysis identified only one significantly enriched pathway (p<0.05), hsa04080: Neuroactive ligand-receptor interaction, among the transcripts. Conclusion: The number of deleterious nsSNPs in YMPs was identified and then these variants-containing genes in YMPs data were adopted as the putative human diseases-related genes. The results revealed that many genes encompassing nsSNPs in YMPs were related to the various human genes which are potentially associated with kidney development and metabolic processes as well as human disease occurrence.

• Genomics & Informatics
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• 제19권1호
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• pp.4.1-4.9
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• 2021

Lip and oral cavity cancer, which can occur in any part of the mouth, is the 11th most common type of cancer worldwide. The major obstacles to patients' survival are the poor prognosis, lack of specific biomarkers, and expensive therapeutic alternatives. This study aimed to identify the main genes and pathways associated with lip and oral cavity carcinoma using network analysis and to analyze its molecular mechanism and prognostic significance further. In this study, 472 genes causing lip and oral cavity carcinoma were retrieved from the DisGeNET database. A protein-protein interaction network was developed for network analysis using the STRING database. VEGFA, IL6, MAPK3, INS, TNF, MAPK8, MMP9, CXCL8, EGF, and PTGS2 were recognized as network hub genes using the maximum clique centrality algorithm available in cytoHubba, and nine potential drug candidates (ranibizumab, siltuximab, sulindac, pomalidomide, dexrazoxane, endostatin, pamidronic acid, cetuximab, and apricoxib) for lip and oral cavity cancer were identified from the DGIdb database. Gene enrichment analysis was also performed to identify the gene ontology categorization of cellular components, biological processes, molecular functions, and biological pathways. The genes identified in this study could furnish a new understanding of the underlying molecular mechanisms of carcinogenesis and provide more reliable biomarkers for early diagnosis, prognostication, and treatment of lip and oral cavity cancer.

• Asian Pacific Journal of Cancer Prevention
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• 제15권5호
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• pp.2273-2278
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• 2014

Purpose: The purpose of our study was to explore the molecular mechanisms in the process of oral squamous cells carcinoma (OSCC) development. Method: We downloaded the affymetrix microarray data GSE31853 and identified differentially expressed genes (DEGs) between OSCC and normal tissues. Then Gene Ontology (GO) and Protein-Protein interaction (PPI) networks analysis was conducted to investigate the DEGs at the function level. Results: A total 372 DEGs with logFCI >1 and P value < 0.05 were obtained, including NNMT, BAX, MMP9 and VEGF. The enriched GO terms mainly were associated with the nucleoplasm, response to DNA damage stimuli and DNA repair. PPI network analysis indicated that GMNN and TSPO were significant hub proteins and steroid biosynthesis and synthesis and degradation of ketone bodies were significantly dysregulated pathways. Conclusion: It is concluded that the genes and pathways identified in our work may play critical roles in OSCC development. Our data provides a comprehensive perspective to understand mechanisms underlying OSCC and the significant genes (proteins) and pathways may be targets for therapy in the future.

• The Plant Pathology Journal
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• 제34권5호
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• pp.435-444
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• 2018

Receptor-like proteins (RLPs) are involved in plant development and disease resistance. Only some of the RLPs in tomato (Solanum lycopersicum L.) have been functionally characterized though 176 genes encoding RLPs, which have been identified in the tomato genome. To further understand the role of RLPs in tomato, we performed genome-guided classification and transcriptome analysis of these genes. Phylogenic comparisons revealed that the tomato RLP members could be divided into eight subgroups and that the genes evolved independently compared to similar genes in Arabidopsis. Based on location and physical clustering analyses, we conclude that tomato RLPs likely expanded primarily through tandem duplication events. According to tissue specific RNA-seq data, 71 RLPs were expressed in at least one of the following tissues: root, leaf, bud, flower, or fruit. Several genes had expression patterns that were tissue specific. In addition, tomato RLP expression profiles after infection with different pathogens showed distinguish gene regulations according to disease induction and resistance response as well as infection by bacteria and virus. Notably, Some RLPs were highly and/or unique expressed in susceptible tomato to pathogen, suggesting that the RLP could be involved in disease response, possibly as a host-susceptibility factor. Our study could provide an important clues for further investigations into the function of tomato RLPs involved in developmental and response to pathogens.

• The Plant Pathology Journal
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• 제18권2호
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• pp.57-62
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• 2002

In vivo expression technology (IVET) has been developed to study bacterial gene expression in Salmonella typhimurium during host infection. The expression of selected genes by IVET has been elevated in vivo but not in vitro. The selected genes turned out to be important for bacterial virulence and/or pathogenicity. IVET depends on a synthetic operon with a promoterless transcriptional fusion between a selection marker gene and a reporter gene. The IVET approach has been successfully adapted in other bacterial pathogens and plant-associated bacteria using different selection markers. Pseudomonas putida suppresses citrus root rot caused by Phytophthora parasitica and enhances citrus seedling growth. The WET strategy was adapted based on a transcriptional fusion, pyrBC'-lacZ, in P. putida to study the bacterial traits important far biocontrol activities. Several genes appeared to be induced on P. parasitica hyphae and were found to be related with metabolism and regulation of gene expression. It is likely that the biocontrol strain took a metabolic advantage from the plant pathogenic fungus and then suppressed citrus root rot effectively. The result was parallel with those from the adaptation of IVET in P. fluorescens, a plant growth promoting rhizobacteria (PGPR). Interestingly, genes encoding components for type III secretion system have been identified as rhizosphere-induced genes in the PGPR strain. The type III secretion system may play a certain role during interaction with its counterpart plants. Application of IVET has been demonstrated in a wide range of bacteria. It is an important strategy to genetically understand complicated bacterial traits in the environment.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.623-626
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• 2006

Group of genes controls the functioning of a cell by complex interactions. These interacting gene groups are called Gene Regulatory Networks (GRNs). Two previous data mining approaches, clustering and classification have been used to analyze gene expression data. While these mining tools are useful for determining membership of genes by homology, they don't identify the regulatory relationships among genes found in the same class of molecular actions. Furthermore, we need to understand the mechanism of how genes relate and how they regulate one another. In order to detect regulatory relationships among genes from time-series Microarray data, we propose a novel approach using frequent pattern mining and chain rule. In this approach, we propose a method for transforming gene expression data to make suitable for frequent pattern mining, and detect gene expression patterns applying FP-growth algorithm. And then, we construct gene regulatory network from frequent gene patterns using chain rule. Finally, we validated our proposed method by showing that our experimental results are consistent with published results.

• The Plant Pathology Journal
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• 제17권2호
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• pp.83-87
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• 2001

Disease resistance in plants is often controlled by gene-for-gene mechanism in which avirulence (avr) gene products encoding by pathogens are specifically recognized, either directly or indirectly by plant disease resistance (R) gene products. Recent studies arising from molecular cloning of a number of R genes from various plant species that confer resistance to different pathogens and corresponding avr genes from various pathogens resulted in the accumulation of a wealth of knowledge on mode of action of gene-for-gene interaction. Specially, members of the NBS-LRR class of R genes encoding proteins containing a nucleotide binding site (NBS) and carboxyl-terminal leucine-rich repeats (LRRs) confer resistance to very different types of phytopathogens, such as bacteria, fungi, oomycetes, viruses, nematodes and aphids. This article reviewed the molecular events that occur up-stream of defense response pathway, specially, bacterial avr gene protein recognition mediated by NBS-LRR type R gene product in plant based on current research results of well studied model plants.

• 대한의생명과학회지
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• 제26권1호
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• pp.28-36
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• 2020

High blood pressure (HTN) is a condition in which blood pressure is kept higher than normal. Blood pressure trait measures systolic blood pressure (SBP) which is the highest pressure and diastolic blood pressure (DBP) which is the lowest blood pressure. Pulse pressure (PP) is the difference between systolic and diastolic blood pressure. Hypertension is known as a disease caused by the interaction of the environment and genetic factors. To date, studies have been conducted to find genes associated with hypertension. Genome-Wide Association Study (GWAS) analysis using European data from the UK Biobank reported new 535 loci were associated with blood pressure trait. Among them, 12 genes have been reported to have a significant correlation with SBP, DBP and PP. In the study, 12 genes polymorphisms were extracted based on KARE (Korean association resource) and then we performed linear regression of blood pressure trait. As a result, 6 SNPs of the 3 genes (rs12355413 and rs11006736 of ARMC4, rs2290883, rs2290884 and rs11039014 of LRP4, rs7234941 of BCL2) showed statistically significant correlation (P<0.05) with blood pressure trait. Of the 3 genes, 6 SNPs in 2 genes (rs9651357, rs12355413, rs11006736, rs1889522 of ARMC4 and rs4987774, rs7234941 of BCL2) showed significant correlation with hypertension. These results suggest that genetic polymorphisms of ARMC4, LRP4 and BCL2 genes are associated with blood pressure traits and hypertension in Korean population. Moreover, we expected to help understand the pathogenesis of hypertension.

• Journal of Korean Neurosurgical Society
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• 제65권1호
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• pp.4-12
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• 2022

Objective : We reported the differentially methylated genes in patients with subarachnoid hemorrhage (SAH) using bioinformatics analyses to explore the biological characteristics of the development of delayed cerebral ischemia (DCI). Methods : DNA methylation profiles obtained from 40 SAH patients from an epigenome-wide association study were analyzed. Functional enrichment analysis, protein-protein interaction (PPI) network, and module analyses were carried out. Results : A total of 13 patients (32.5%) experienced DCI during the follow-up. In total, we categorized the genes into the two groups of hypermethylation (n=910) and hypomethylation (n=870). The hypermethylated genes referred to biological processes of organic cyclic compound biosynthesis, nucleobase-containing compound biosynthesis, heterocycle biosynthesis, aromatic compound biosynthesis and cellular nitrogen compound biosynthesis. The hypomethylated genes referred to biological processes of carbohydrate metabolism, the regulation of cell size, and the detection of a stimulus, and molecular functions of amylase activity, and hydrolase activity. Based on PPI network and module analysis, three hypermethylation modules were mainly associated with antigen-processing, Golgi-to-ER retrograde transport, and G alpha (i) signaling events, and two hypomethylation modules were associated with post-translational protein phosphorylation and the regulation of natural killer cell chemotaxis. VHL, KIF3A, KIFAP3, RACGAP1, and OPRM1 were identified as hub genes for hypermethylation, and ALB and IL5 as hub genes for hypomethylation. Conclusion : This study provided novel insights into DCI pathogenesis following SAH. Differently methylated hub genes can be useful biomarkers for the accurate DCI diagnosis.

• Genomics & Informatics
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• 제21권3호
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• pp.36.1-36.19
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• 2023

The LIM domain-containing proteins are dominantly found in plants and play a significant role in various biological processes such as gene transcription as well as actin cytoskeletal organization. Nevertheless, genome-wide identification as well as functional analysis of the LIM gene family have not yet been reported in the economically important plant sorghum (Sorghum bicolor L.). Therefore, we conducted an in silico identification and characterization of LIM genes in S. bicolor genome using integrated bioinformatics approaches. Based on phylogenetic tree analysis and conserved domain, we identified five LIM genes in S. bicolor (SbLIM) genome corresponding to Arabidopsis LIM (AtLIM) genes. The conserved domain, motif as well as gene structure analyses of the SbLIM gene family showed the similarity within the SbLIM and AtLIM members. The gene ontology (GO) enrichment study revealed that the candidate LIM genes are directly involved in cytoskeletal organization and various other important biological as well as molecular pathways. Some important families of regulating transcription factors such as ERF, MYB, WRKY, NAC, bZIP, C2H2, Dof, and G2-like were detected by analyzing their interaction network with identified SbLIM genes. The cis-acting regulatory elements related to predicted SbLIM genes were identified as responsive to light, hormones, stress, and other functions. The present study will provide valuable useful information about LIM genes in sorghum which would pave the way for the future study of functional pathways of candidate SbLIM genes as well as their regulatory factors in wet-lab experiments.