• Microbiology and Biotechnology Letters
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• v.52 no.2
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• pp.163-178
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• 2024

Pan-genome analysis is used to interpret genome heterogeneity and diversification of bacterial species. Here, we present pan-genome analysis of 22 strains of Enterococcus mundtii. The GenBank file of E. mundtii strains that have been isolated from different sources i.e., human fecal matter, soil, leaf, dairy products, and insects was downloaded from National Center for Biotechnology Information (NCBI) database and analyzed using BPGA-1.3.0 (Bacterial Pan Genome Analysis) pipeline. Out of a total, 4503 gene families, 1843 belongs to the core genes whereas 1,762 gene families represent the accessory genes and 898 gene families depict the unique genes among all the selected genomes. Majority of the core genes belongs to the categories of Metabolism (37.83%) and Information storage & processing (29.84%) whereas unique genes belongs to the category of Information storage & processing (48.08%). Further, accessory genes are almost equally present in both functional categories i.e. Information storage & processing and Metabolism (34.34% and 32.27% respectively). Further, subset analysis on the basis of the origin of isolates exhibits presence and absence of exclusive gene families. The observation suggests that even closely related strains of a species show extensive disparity in genome owing to their ability to adapt to a specific environment.

• Journal of Microbiology and Biotechnology
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• v.19 no.2
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• pp.140-146
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• 2009

MAPSI(Management and Analysis for Polyketide Synthase Type I) has been developed to offer computational analysis methods to detect type I PKS(polyketide synthase) gene clusters in genome sequences. MAPSI provides a genome analysis component, which detects PKS gene clusters by identifying domains in proteins of a genome. MAPSI also contains databases on polyketides and genome annotation data, as well as analytic components such as new PKS assembly and domain analysis. The polyketide data and analysis component are accessible through Web interfaces and are displayed with diverse information. MAPSI, which was developed to aid researchers studying type I polyketides, provides diverse components to access and analyze polyketide information and should become a very powerful computational tool for polyketide research. The system can be extended through further studies of factors related to the biological activities of polyketides.

• 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.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.153-159
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• 2005

Microarray gene expression technology has applications that could refine diagnosis and therapeutic monitoring as well as improve disease prevention through risk assessment and early detection. Especially, microarray expression data can provide important information regarding specific genes related with metastasis through an appropriate analysis. Various methods for clustering analysis microarray data have been introduced so far. We used twostep clustering fot ascertain metastasis related gene through t-test. Through t-test between two groups for two publicly available medulloblastoma microarray data sets, we intended to find significant gene for metastasis. The paper describes the process in detail showing how the process is applied to clustering analysis and t-test for microarray datasets and how the metastasis-associated genes are explorated.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1005-1021
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• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.598-600
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• 2001

DNA chip technology enables us to monitor thousands of gene expressions per sample simultaneously. Typically, DNA microarray data has at least several thousands of variables (genes) wish relatively smal1 number of samples. Thus feature (gene) selection by dimensionality reduction is necessary for efficient data analysis. In this paper we employ the partial least squares (PLS) method for gene selection and the principal component analysis (PCA) method for classification. The useful behavior of the PLS is verified by computer simulations.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1529-1540
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• 2011

Silencing of a specific gene using RNAi (RNA interference) is a valuable tool for functional analysis of a target gene. However, information on RNAi for analysis of gene function in farm animals is relatively nil. In the present study, we have validated the interfering effects of siRNA (small interfering RNA) using both quantitative and qualitative gene silencing in buffalo granulosa cells. Qualitative gene knockdown was validated using a fluorescent vector, enhanced green fluorescence protein (EGFP) and fluorescently labeled siRNA (Cy3) duplex. While quantitatively, siRNA targeted against the luciferase and CYP19 mRNA was used to validate the technique. CYP19 gene, a candidate fertility gene, was selected as a model to demonstrate the technique optimization. However, to sustain the expression of CYP19 gene in culture conditions using serum is difficult because granulosa cells have the tendency to luteinize in presence of serum. Therefore, serum free culture conditions were optimized for transfection and were found to be more suitable for the maintenance of CYP19 gene transcripts in comparison to culture conditions with serum. Decline in fluorescence intensity of green fluorescent protein (EGFP) was observed following co-transfection with plasmid generating siRNA targeted against EGFP gene. Quantitative decrease in luminescence was seen when co-transfected with siRNA against the luciferase gene. A significant suppressive effect on the mRNA levels of CYP19 gene at 100 nM siRNA concentration was observed. Also, measurement of estradiol levels using ELISA (enzyme-linked immunosorbent assay) showed a significant decline in comparison to control. In conclusion, the present study validated gene silencing using RNAi in cultured buffalo granulosa cells which can be used as an effective tool for functional analysis of target genes.

• Genomics & Informatics
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• v.15 no.2
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• pp.56-64
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• 2017

We have previously reported that NS-398, a cyclooxygenase-2 (COX-2)-selective inhibitor, inhibited replicative cellular senescence in human dermal fibroblasts and skin aging in hairless mice. In contrast, celecoxib, another COX-2-selective inhibitor, and aspirin, a non-selective COX inhibitor, accelerated the senescence and aging. To figure out causal factors for the senescence-modulating effect of the inhibitors, we here performed cDNA microarray experiment and subsequent Gene Set Enrichment Analysis. The data showed that several senescence-related gene sets were regulated by the inhibitor treatment. NS-398 up-regulated gene sets involved in the tumor necrosis factor ${\beta}$ receptor pathway and the fructose and mannose metabolism, whereas it down-regulated a gene set involved in protein secretion. Celecoxib up-regulated gene sets involved in G2M checkpoint and E2F targets. Aspirin up-regulated the gene set involved in protein secretion, and down-regulated gene sets involved in RNA transcription. These results suggest that COX inhibitors modulate cellular senescence by different mechanisms and will provide useful information to understand senescence-modulating mechanisms of COX inhibitors.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1331-1339
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• 2013

The lipoprotein lipase (LPL) gene can be considered a functional candidate gene that regulates fatty acid composition. Oh etc (2013) investigated the relationship between unsaturated fatty acids and five novel SNPs, and had confirmed that three polymorphic SNPs (c.322G>A, c.329A>T and c.1591G>A) were associated with fatty acid composition. We have used generalized linear model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. We applied the MDR method on the identify major interaction effects of exonic single nucleotide polymorphisms (SNPs) in the LPL gene for economic traits in Korean cattles population.

• Korean Journal of Veterinary Research
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• v.39 no.4
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• pp.797-805
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• 1999

T sergenti cDNA library were constructed to get a more broad information about the structural, functional or antigenic properties of the proteins, and analyzes for their partial cDNA sequences and expression sequences tags(ESTg). The mRNA were purified from T sergenti isolates to identify the information of antigen gene, then first and second strand cDNA was synthesized. EcoR I adaptor ligation and Xho I enzyme restriction were used to the synthesized cDNA, and ligated into a Uni-ZAP XR vector. T sergenti cDNA library was constructed with packaging and amplification in vitro. Antibody screening was performed with constructed T sergenti cDNA library using antisera against T sergenti. Among those clones, eight phagemids were rescued from the recombinant in vivo excision with f1 helper phage. Using the analysis of endonuclease restriction and PCR, the recombinant cDNA were proved having a 0.5-3.0kb of inserts. The eight of partial cDNA clones' sequences were obtained and examined for their homology using BLASTN and BLASTX. The eight of sequenced clones were classified into three groups according to the basis of database searches. A total 3,045bp of partial cDNA sequence were determined from six clones. The putatively identified clones contain a cytochrome c gene, a heat shock protein gene, a cyclophilin gene, and a ribosomal protein gene. The unidentified clones have a homology to ATP-binding protein(mtrA) gene of S argillaceus, DNA-binding protein(DBP) gene of Pseudorabies virus 85kDa merozoite protein gene of B bovis, mRNA spm1 protein of T annulata and glycine-rich RNA-binding protein mRNA of O sativa etc.