• The Plant Pathology Journal
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• v.29 no.3
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• pp.249-259
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• 2013

Burkholderia glumae causes rice grain rot and sheath rot by producing toxoflavin, the expression of which is regulated by quorum sensing (QS). The QS systems of B. glumae rely on N-octanoyl homoserine lactone, synthesized by TofI and its cognate receptor TofR, to activate the genes for toxoflavin biosynthesis and an IclR-type transcriptional regulator gene, qsmR. To understand genome-wide transcriptional profiling of QS signaling, we employed RNAseq of the wild-type B. glumae BGR1 with QS-defective mutant, BGS2 (BGR1 tofI::${\Omega}$) and QS-dependent transcriptional regulator mutant, BGS9 (BGR1 qsmR::${\Omega}$). A comparison of gene expression profiling among the wild-type BGR1 and the two mutants before and after QS onset as well as gene ontology (GO) enrichment analysis from differential expressed genes (DEGs) revealed that genes involved in motility were highly enriched in TofI-dependent DEGs, whereas genes for transport and DNA polymerase were highly enriched in QsmR-dependent DEGs. Further, a combination of pathways with these DEGs and phenotype analysis of mutants pointed to a couple of metabolic processes, which are dependent on QS in B. glumae, that were directly or indirectly related with bacterial motility. The consistency of observed bacterial phenotypes with GOs or metabolic pathways in QS-regulated genes implied that integration RNAseq with GO enrichment or pathways would be useful to study bacterial physiology and phenotypes.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.197-207
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• 2010

Using a variety of data-mining methods on high-throughput cDNA microarray data, the level of gene expression in two different tissues can be compared, and DEG(Differentially Expressed Gene) genes in between normal cell and tumor cell can be detected. Diagnosis can be made with these genes, and also treatment strategy can be determined according to the cancer stages. Existing cancer classification methods using machine learning select the marker genes which are differential expressed in normal and tumor samples, and build a classifier using those marker genes. However, in addition to the differences in gene expression levels, the difference in gene-gene correlations between two conditions could be a good marker in disease diagnosis. In this study, we identify gene pairs with a big correlation difference in two sets of samples, build gene classification modules using these gene pairs. This cancer classification method using gene modules achieves higher accuracy than current methods. The implementing clinical kit can be considered since the number of genes in classification module is small. For future study, Authors plan to identify novel cancer-related genes with functionality analysis on the genes in a classification module through GO(Gene Ontology) enrichment validation, and to extend the classification module into gene regulatory networks.

• Journal of Periodontal and Implant Science
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• v.41 no.4
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• pp.192-200
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• 2011

Purpose: The aim of this study is to compare the gene expression profile in mesenchymal stem cells derived from dental tissues and bone marrow for characterization of dental stem cells. Methods: We employed GeneChip analysis to the expression levels of approximately 32,321 kinds of transcripts in 5 samples of bone-marrow-derived mesenchymal stem cells (BMSCs) (n=1), periodontal ligament stem cells (PDLSCs) (n=2), and dental pulp stem cells (DPSCs) (n=2). Each cell was sorted by a FACS Vantage Sorter using immunocytochemical staining of the early mesenchymal stem cell surface marker STRO-1 before the microarray analysis. Results: We identified 379 up-regulated and 133 down-regulated transcripts in BMSCs, 68 up-regulated and 64 down-regulated transcripts in PDLSCs, and 218 up-regulated and 231 down-regulated transcripts in DPSCs. In addition, anatomical structure development and anatomical structure morphogenesis gene ontology (GO) terms were over-represented in all three different mesenchymal stem cells and GO terms related to blood vessels, and neurons were over-represented only in DPSCs. Conclusions: This study demonstrated the genome-wide gene expression patterns of STRO-$1^+$ mesenchymal stem cells derived from dental tissues and bone marrow. The differences among the expression profiles of BMSCs, PDLSCs, and DPSCs were shown, and 999 candidate genes were found to be definitely up- or down-regulated. In addition, GOstat analyses of regulated gene products provided over-represented GO classes. These data provide a first step for discovering molecules key to the characteristics of dental stem cells.

• Journal of Animal Science and Technology
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• v.62 no.6
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• pp.765-776
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• 2020

The retinal degenerative disease, progressive retinal atrophy (PRA) is a major reason of vision impairment in canine population. Canine PRA signifies an inherently dissimilar category of retinal dystrophies which has solid resemblances to human retinis pigmentosa. Even though much is known about the biology of PRA, the knowledge about the intricate connection among genetic loci, genes and pathways associated to this disease in dogs are still remain unknown. Therefore, we have performed a genome wide association study (GWAS) to identify susceptibility single nucleotide polymorphisms (SNPs) of PRA. The GWAS was performed using a case-control based association analysis method on PRA dataset of 129 dogs and 135,553 markers. Further, the gene-set and pathway analysis were conducted in this study. A total of 1,114 markers associations with PRA trait at p < 0.01 were extracted and mapped to 640 unique genes, and then selected significant (p < 0.05) enriched 35 gene ontology (GO) terms and 5 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways contain these genes. In particular, apoptosis process, homophilic cell adhesion, calcium ion binding, and endoplasmic reticulum GO terms as well as pathways related to focal adhesion, cyclic guanosine monophosphate)-protein kinase G signaling, and axon guidance were more likely associated to the PRA disease in dogs. These data could provide new insight for further research on identification of potential genes and causative pathways for PRA in dogs.

• Parasites, Hosts and Diseases
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• v.59 no.1
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• pp.67-76
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• 2021

Legionella pneumophila is an opportunistic pathogen that survives and proliferates within protists such as Acanthamoeba spp. in environment. However, intracellular pathogenic endosymbiosis and its implications within Acanthamoeba spp. remain poorly understood. In this study, RNA sequencing analysis was used to investigate transcriptional changes in A. castellanii in response to L. pneumophila infection. Based on RNA sequencing data, we identified 1,211 upregulated genes and 1,131 downregulated genes in A. castellanii infected with L. pneumophila for 12 hr. After 24 hr, 1,321 upregulated genes and 1,379 downregulated genes were identified. Gene ontology (GO) analysis revealed that L. pneumophila endosymbiosis enhanced hydrolase activity, catalytic activity, and DNA binding while reducing oxidoreductase activity in the molecular function (MF) domain. In particular, multiple genes associated with the GO term 'integral component of membrane' were downregulated during endosymbiosis. The endosymbiont also induced differential expression of various methyltransferases and acetyltransferases in A. castellanii. Findings herein are may significantly contribute to understanding endosymbiosis of L. pneumophila within A. castellanii.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.5
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• pp.609-624
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• 2013

The objective of this study was to get a comprehensive understanding of how genes in chicken shell gland modulate eggshell strength at the early stage of active calcification. Four 32-week old of purebred Xianju hens with consistent high or low shell breakage strength were grouped into two pairs. Using Affymetrix Chicken Array, a whole-transcriptome analysis was performed on hen's shell gland at 9 h post oviposition. Gene ontology enrichment analysis for differentially expressed (DE) transcripts was performed using the web-based GOEAST, and the validation of DE-transcripts was tested by qRT-PCR. 1,195 DE-transcripts, corresponding to 941 unique genes were identified in hens with strong eggshell compared to weak shell hens. According to gene ontology annotations, there are 77 DE-transcripts encoding ion transporters and secreted extracellular matrix proteins, and at least 26 DE-transcripts related to carbohydrate metabolism or post-translation glycosylation modification; furthermore, there are 88 signaling DE-transcripts. GO term enrichment analysis suggests that some DE-transcripts mediate reproductive hormones or neurotransmitters to affect eggshell quality through a complex suite of biophysical processes. These results reveal some candidate genes involved with eggshell strength at the early stage of active calcification which may facilitate our understanding of regulating mechanisms of eggshell quality.

• Journal of Animal Science and Technology
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• v.66 no.4
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• pp.702-716
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• 2024

The objective of this study was to identify genomic regions and candidate genes associated with productive traits using a total of 37,099 productive records and 6,683 single nucleotide polymorphism (SNP) data obtained from five Great-Grand-Parents (GGP) farms in Landrace. The estimated of heritabilities for days to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) were 0.49, 0.49, 0.56, and 0.23, respectively. We identified a genetic window that explained 2.05%-2.34% for each trait of the total genetic variance. We observed a clear partitioning of the four traits into two groups, and the most significant genomic region for AGE and ADG were located on the Sus scrofa chromosome (SSC) 1, while BF and EMA were located on SSC 2. We conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), which revealed results in three biological processes, four cellular component, three molecular function, and six KEGG pathway. Significant SNPs can be used as markers for quantitative trait loci (QTL) investigation and genomic selection (GS) for productive traits in Landrace pig.

• Genomics & Informatics
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• v.19 no.4
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• pp.39.1-39.8
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• 2021

Tamoxifen (TAM) is an anticancer drug used to treat estrogen receptor (ER)-positive breast cancer. However, its ER-independent cytotoxic and antifungal activities have prompted debates on its mechanism of action. To achieve a better understanding of the ER-independent antifungal action mechanisms of TAM, we systematically identified TAM-sensitive genes through microarray screening of the heterozygous gene deletion library in fission yeast (Schizosaccharomyces pombe). Secondary confirmation was followed by a spotting assay, finally yielding 13 TAM-sensitive genes under the drug-induced haploinsufficient condition. For these 13 TAM-sensitive genes, we conducted a comparative analysis of their Gene Ontology (GO) 'biological process' terms identified from other genome-wide screenings of the budding yeast deletion library and the MCF7 breast cancer cell line. Several TAM-sensitive genes overlapped between the yeast strains and MCF7 in GO terms including 'cell cycle' (cdc2, rik1, pas1, and leo1), 'signaling' (sck2, oga1, and cki3), and 'vesicle-mediated transport' (SPCC126.08c, vps54, sec72, and tvp15), suggesting their roles in the ER-independent cytotoxic effects of TAM. We recently reported that the cki3 gene with the 'signaling' GO term was related to the ER-independent antifungal action mechanisms of TAM in yeast. In this study, we report that haploinsufficiency of the essential vps54 gene, which encodes the GARP complex subunit, significantly aggravated TAM sensitivity and led to an enlarged vesicle structure in comparison with the SP286 control strain. These results strongly suggest that the vesicle-mediated transport process might be another action mechanism of the ER-independent antifungal or cytotoxic effects of TAM.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.137-147
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• 2015

This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. We identify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson's correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients with estrogen-receptor-negative using the network as a classifier. We compare classification performance of our algorithm with existing algorithms on independent data and shows our algorithm is improved. In addition, we make an functionality analysis on the genes in the prognosis-specific network using GO(Gene Ontology) enrichment validation.

• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.