• Genomics & Informatics
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• v.3 no.1
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• pp.30-34
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• 2005

Microarray technology makes it possible to measure the expressions of tens of thousands of genes simultaneously under various experimental conditions. Identifying differentially expressed genes in each single experimental condition is one of the most common first steps in microarray gene expression data analysis. Reasonable choices of thresholds for determining differentially expressed genes are used for the next-stap-analysis with suitable statistical significances. We present a supervised model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are trying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful structure from microarray datasets.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.148-148
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• 2019

Wheat is a very important crop as a food source worldwide, but gluten in wheat causes a variety of allergic reactions. Previous studies have developed ${\omega}-5$ gliadin deleted O-free, known as the central antigen of WDEIA (wheat-dependent exercise-induced anaphylaxis). In this study, we performed RNA sequencing on the grains and leaves of the allergic-reduced species O-free and their cultivars, Keumkang and Olgeuru, to analyze differentially expressed genes (DEG) based on different cultivars and tissues. Tissues of all species were biologically repeated three times. We used bowtie2 version 2.3.5.1 to get sequence data from RNAseq and used cufflinks and Tophat programs to find DEG. When comparing leaf and grain tissues, a total of 1,244 DEGs were found in the leaf tissues while only 563 DEGs were found in the grain tissues. As a result of gene ontology analysis of differentially expressed genes, the leaf tissues were mostly included in the "catalytic activity" part of molecular function, "metabolic process" part of biological process, and "membrane" part of cell component. The grain tissues were mostly included in the "metabolic process" part of biological process, "binding" and "catalytic activity" part of molecular function, and "membrane, cell, cell part" parts of cell component. Based on these results, we present information on the differentially expressed genes of the three cultivars of leaves and grains. This study could be an important basis for studying the characteriztion of O-free.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.124-130
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• 2004

Microarray expression datasets are incessantly cumulated with the aid of recent technological advances. One of the first steps for analyzing these data under various experimental conditions is determining differentially expressed genes (DEGs) in each condition. Reasonable choices of thresholds for determining differentially expressed genes are used for the next -step-analysis with suitable statistical significances. We present a model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are tying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful network structure from microarray datasets.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.24
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• pp.10797-10801
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• 2015

Background: To explore the molecular mechanisms of metastatic osteosarcoma (OS) by using the microarray expression profiles of metastatic and non-metastatic OS samples. Materials and Methods: The gene expression profile GSE37552 was downloaded from Gene Expression Omnibus database, including 2 human metastatic OS cell line models and 2 two non-metastatic OS cell line models. The differentially expressed genes (DEGs) were identified by Multtest package in R language. In addition, functional enrichment analysis of the DEGs was performed by WebGestalt, and the protein-protein interaction (PPI) networks were constructed by Hitpredict, then the signal pathways of the genes involved in the networks were performed by Kyoto Encyclopaedia of Genes and Genomes (KEGG) automatic annotation server (KAAS). Results: A total of 237 genes were classified as DEGs in metastatic OS. The most significant up- and down-regulated genes were A2M (alpha-2-macroglobulin) and BCAN (brevican). The DEGs were significantly related to the response to hormone stimulus, and the PPI network of A2M contained IL1B (interleukin), LRP1 (low-density lipoprotein receptor-related protein 1) and PDGF (platelet-derived growth factor). Furthermore, the MAPK signaling pathway and focal adhesion were significantly enriched. Conclusions: A2M and its interactive proteins, such as IL1B, LRP1 and PDGF may be candidate target molecules to monitor, diagnose and treat metastatic OS. The response to hormone stimulus, MAPK signaling pathway and focal adhesion may play important roles in metastatic OS.

• Toxicological Research
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• v.25 no.3
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• pp.119-124
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• 2009

Genes related to Mycoplasma hyopneumoniae-induced inflammation were identified using the genefishing technology, an improved method for identifying differentially expressed genes (DEGs) using an annealing control primer (ACP) system in RAW264.7 cells. After treatment with M. hyopneumoniae, 16 DEGs were expressed in RAW264.7 cells using a pre-screening system. Among these 16 DEGs, 11 DEGs (DEGs 1, 4, 5-10, 12-15) were selected and sequenced directly, revealing that DEG12 (Grap), DEG14 (Gadd45), and DEG15 (secreted phosphoprotein 1) were related to inflammatory cytokines. This is the first report that intact M. hyopneumoniae induces the expression of Grap, Gadd 45${\beta}$, and secreted phosphoprotein 1 in RAW264.7 cells. Subsequently, these genes may be targets for screening novel inhibitors of the mycoplasmal inflammatory response.

• Archives of Plastic Surgery
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• v.34 no.6
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• pp.671-678
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• 2007

Purpose: Venous malformation(VM) which often causes pain and discomfort is the most common type of vascular malformations. Although it is presented with disfigured appearance and associated soft tissue or skeletal hypertrophy, the molecular bases of VMs are poorly understood. Differentially expressed genes(DEGs) of VMs were investigated to illuminate the molecular mechanism of the disease entity. Methods: Gene expressions of VM patients' subcutaneous tissue were studied in comparison with normal persons' by $GeneFishing^{TM}$ technique using the annealing control primers (ACPs) to identify DEGs. Candidate genes were sequenced and screened by basic local alignment search tool (BLAST) afterwards. Results: Among seventy DEGs identified, forty DEGs which had shown significantly different expression pattern were sequenced. Twenty eight out of 40 were up-regulated while 12 were down-regulated. BLAST searches revealed that 37 were known genes and 3 were unknown genes. Many genes were involved in the differentiation and remodeling of smooth muscle cells, opposed to the previous hypothesis that a lot of angiogenetic genes would be involved. Furthermore, several transcription factors and related genes, as well as cell signaling and metabolism regulators, were up regulated. Conclusion: It suggests that analysis of DEGs in VMs provide basic knowledge about its pathophysiology. and new therapeutic approaches.

• Journal of Plant Biotechnology
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• v.43 no.2
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• pp.204-212
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• 2016

To understand the responses of grapevines in response to cold stress causing the limited growth and development, differentially expressed genes (DEGs) were screened through transcriptome analysis of shoots from 2 grapevine cultivars ('Campbell Early' and 'Muscat Baily A') kept at -$2^{\circ}C$ for 4 days. In gene ontology analysis of DEGs from 'Campbell Early', there were 17,424 clones related with biological process, 28,954 with cellular component, and 6,972 with molecular function genes in response to freezing temperature. The major induced genes included dehydrin xero 1, K-box region and MADS-box transcription factor family protein, and MYB domain protein 36, and inhibited genes included light-harvesting chlorophyll B-binding protein 3, FASCICLIN-like arabinoogalactan 9, and pectin methylesterase 61 in 'Campbell Early' grapevines. In gene ontology analysis of DEGs from 'Muscat Baily A', there were 1,157 clones related with biological process, 1,350 with cellular component, and 431 with molecular function gene. The major induced genes of 'Muscat Baily A' included NB-ARC domain-containing disease resistance protein, fatty acid hydrozylase superfamily, and isopentenyltransferase 3, and inhibited genes included binding, IAP-like protein 1, and pentatricopeptide repeat superfamily protein. All major DEGs were shown to be expressed differentially by freezing temperature in real time-PCR analysis. Protein domain analysis using InterPro Scan revealed that ubiquitin-protein ligase was redundant in both tested grapevines. Transcriptome profile of shoots exposed to cold can provide new insights into the molecular basis of tolerance to low-temperature in grapevines, and can be used as resources for development new grapevines tolerant to coldness.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.10
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• pp.1496-1511
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• 2015

The study aimed to compare the necrotic enteritis (NE)-induced transcriptome differences between the spleens of Marek's disease resistant chicken line 6.3 and susceptible line 7.2 co-infected with Eimeria maxima/Clostridium perfringens using RNA-Seq. Total RNA from the spleens of two chicken lines were used to make libraries, generating 42,736,296 and 42,617,720 usable reads, which were assembled into groups of 29,897 and 29,833 mRNA genes, respectively. The transcriptome changes were investigated using the differentially expressed genes (DEGs) package, which indicated 3,255, 2,468 and 2,234 DEGs of line 6.3, line 7.2, and comparison between two lines, respectively (fold change ${\geq}2$, p<0.01). The transcription levels of 14 genes identified were further examined using qRT-PCR. The results of qRT-PCR were consistent with the RNA-seq data. All of the DEGs were analysed using gene ontology terms, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the DEGs in each term were found to be more highly expressed in line 6.3 than in line 7.2. RNA-seq analysis indicated 139 immune related genes, 44 CD molecular genes and 150 cytokines genes which were differentially expressed among chicken lines 6.3 and 7.2 (fold change ${\geq}2$, p<0.01). Novel mRNA analysis indicated 15,518 novel genes, for which the expression was shown to be higher in line 6.3 than in line 7.2 including some immune-related targets. These findings will help to understand host-pathogen interaction in the spleen and elucidate the mechanism of host genetic control of NE, and provide basis for future studies that can lead to the development of marker-based selection of highly disease-resistant chickens.

• Journal of Applied Biological Chemistry
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• v.51 no.1
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• pp.1-6
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• 2008

Estrogens, a group of steroid compounds functioning as the primary female sex hormone, play an important role in the development and progression of breast cancer. In this study, using a novel annealing control primer-based GeneFishing PCR technology, five differentially expressed genes (DEGs), expressed using 10nM mitogenic estrogens, $17{\beta}$-estradiol (E2) and $16{\alpha}$-hydroxyestrone ($16{\alpha}$-OHE1), were selected from the estrogen receptor (ER)-positive MCF-7 human breast cancer cells. The DEGs, MRPL42, TUBA1B, SSBP1, KNCT2, and RUVBL1, were identified by comparison with the known genes via direct sequencing and sequence homology search in BLAST. Quantitative real-time PCR data showed that two DEGs, tubulin ${\alpha}1b$ and kinetochore associated 2, were greater than 2-fold upregulated by E2 or $16{\alpha}$-OHE1. Both genes could be new biomarkers for the treatment and prognosis of cancers, and further study may provide insights into the molecular mechanisms underlying development and progression of breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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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.