• BMB Reports
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• v.37 no.5
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• pp.546-551
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• 2004

The increasing pace of development in molecular biology during the last decade has had a direct effect on mass testing and diagnostic applications, including blood screening. We report the model Microarray that has been developed for Hepatitis B virus (HBV) and Hepatitis D virus (HDV) detection. The specific primer pairs of PCR were designed using the Primer Premier 5.00 program according to the conserved regions of HBV and HDV. PCR fragments were purified and cloned into pMD18-T vectors. The recombinant plasmids were extracted from positive clones and the target gene fragments were sequenced. The DNA microarray was prepared by robotically spotting PCR products onto the surface of glass slides. Sequences were aligned, and the results obtained showed that the products of PCR amplification were the required specific gene fragments of HBV, and HDV. Samples were labeled by Restriction Display PCR (RD-PCR). Gene chip hybridizing signals showed that the specificity and sensitivity required for HBV and HDV detection were satisfied. Using PCR amplified products to construct gene chips for the simultaneous clinical diagnosis of HBV and HDV resulted in a quick, simple, and effective method. We conclude that the DNA microarray assay system might be useful as a diagnostic technique in the clinical laboratory. Further applications of RD-PCR for the sample labeling could speed up microarray multi-virus detection.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2519-2525
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• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• Genomics & Informatics
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• v.10 no.1
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• pp.23-32
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• 2012

There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

• The Plant Pathology Journal
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• v.25 no.2
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• pp.172-178
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• 2009

To obtain global gene expression profiles of Arabidopsis thaliana by acid stress, seedlings were subjected to low pH stress. Using Affymetrix AH1 chips covering 24,000 genes, we analyzed gene expression patterns. Fifty-four genes were up-regulated, and 38 were down-regulated more than 3-fold after 2 h of acid stress (pH 3.0). Several defense and abiotic stress-related genes were recognized among the up-regulated genes and peroxidase and extensin genes were identified among the down-regulated genes. After 12 h treatment, relatively fewer genes showed changed expression, indicating that plants seem to adjust themselves to this abiotic stress. Most of the up-regulated genes are already known to be involved in abiotic stress responses and pathogen attacks, especially wounding. However, down-regulated genes for the members of extensins and peroxidases are specific to the acid treatment. These results suggest that acid treatment turns on genes involved in stress responses, especially in wounding and turns off genes very specific for the acid stress.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.59-60
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• 2000

The past few years have seen a dramatic increase in gene expression data on the basis of DNA microarrays or DNA chips. Going beyond a generic view on the genome, microarray data are able to distinguish between gene populations in different tissues of the same organism and in different states of cells belonging to the same tissue. This affords a cell-wide view of the metabolic and regulatory processes under different conditions, building an effective basis for new diagnoses and therapies of diseases. In this talk we present machine learning techniques for effective mining of DNA microarray data. A brief introduction to the research field of machine learning from the computer science and artificial intelligence point of view is followed by a review of recently-developed learning algorithms applied to the analysis of DNA chip gene expression data. Emphasis is put on graphical models, such as Bayesian networks, latent variable models, and generative topographic mapping. Finally, we report on our own results of applying these learning methods to two important problems: the identification of cell cycle-regulated genes and the discovery of cancer classes by gene expression monitoring. The data sets are provided by the competition CAMDA-2000, the Critical Assessment of Techniques for Microarray Data Mining.

• Biomolecules & Therapeutics
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• v.18 no.4
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• pp.411-419
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• 2010

Korean mistletoe has a variety of biological effects, such as immunoadjuvant activities. This study investigates the effects of Korean mistletoe lectin (Viscum album L. var. coloratum agglutinin, VCA) on human T lymphocytes to determine whether VCA acts as an immunomodulator. Purified human T-lymphocytes were cultured with VCA and RNA from each point was analyzed using Affymetrix human genome chips containing 22,500 probe sets which represents more than 18,000 transcripts derived from 14,500 human genes. As a result, there was a striking upregulation of genes coding for chemokines. Seventeen genes out of 50 coding for proteins with chemokine activity were upregulated including CXCL9 and IL-8 which are related to the treatment of cancer. In addition, 28 cytokine genes were upregulated including IL-1, IL-6, IL-8, IFN-$\gamma$, and TNF-$\alpha$. Taken together, the data suggest that Korean mistletoe lectin, in parallel with European mistletoe, has an ability to modulate human T cell function.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.8
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• pp.1127-1133
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• 2018

Objective: Genome wide association study was conducted to identify and validate candidate genes associated with fatty acid composition of pork. Methods: A total of 480 purebreed Duroc pigs were genotyped using IlluminaPorcine60k bead chips while the association test was implemented following genome-wide rapid association using Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach. Results: A total of 25, 29, and 16 single nucleotide polymorphisms (SNPs) were significantly associated with stearic (18:0), oleic (18:1) and saturated fatty acids (SFA), respectively. Genome wide significant variants were located on the same region of swine chromosome 14 (SSC14) that spanned from 120 to 124 Mb. Top SNP ALGA008191 was located at 5 kb near the stearoyl-CoA desaturase (SCD) gene. This gene is directly involved in desaturation of stearic acid into oleic acid. General relationship of significant SNPs showed high linkage disequilibrium thus genome-wide signals was attributed to SCD gene. However, understanding the role of other genes like elongation of very long chain fatty acids-3 (ELOVL3) located on this chromosomal segment might help in further understanding of metabolism and biosynthesis of fatty acids. Conclusion: Overall, this study provides evidence that validates SCD gene as strong candidate gene associated with fatty acid composition in Duroc pigs. Moreover, this study confirms significant SNPs near ELOVL3 gene.

• Journal of Biosystems Engineering
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• v.28 no.5
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• pp.429-438
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• 2003

This study exploits the robot system which is necessary in gene study and bio-technology industry. As well, a DNA chip, which of use has been increased recently, can be manufactured with this system. The robot consists of a device spotting DNA on the silylated slide, a well plate, a bed for fixing well plates, devices of washing and drying the pin in DNA spotting .device, a distillation-water vessel, and a discharge vessel of wash water. We made the period of sticking DNA to the pin on the well plate to be 15 seconds. The spot size of DNA was set to be 0.28 mm on the average by bringing the slide into contact with pin during 1 second. If DNA is spotted in minimum space possible about 0.32mm, this system can stick about 8,100 DNA spots on the well plate with this rate. Analyzing the procedure: Movement starts, Pin washes, dries, and smears DNA on the well plate. Spotting DNA onto 12 chips took 2 minutes and 50 seconds.

• Journal of Animal Science and Technology
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• v.55 no.4
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• pp.231-235
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• 2013

Carcass weight (CW) is one of the most important economic traits in pigs, directly affecting the income of farmers. In this study, a genome wide association study was performed to detect significant single nucleotide polymorphisms (SNPs) affecting CW in pigs derived from a $F_2$ intercross between Landrace and Korean native pig (KNP). Using high-density porcine SNP chips, highly significant SNPs were identified on SSC12. Two candidate genes, LOC100523510 and LOC100621652, were subsequently selected within this region and further investigated. Within these candidate genes, five SNPs were identified and genotyped using the VeraCode GoldenGate assay. The results revealed that one SNP in the LOC100621652 gene and four SNPs in the LOC100523510 gene are highly associated with CW. These SNP markers can thus have significant applications for improving CW in KNP. However, the functions of these candidate genes are not fully understood and require further study.

• Genomics & Informatics
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• v.5 no.4
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• pp.152-160
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• 2007

Most common diseases are caused by multiple genetic and environmental factors. Among the genetic factors, single nucleotide polymorphisms (SNPs) are common DNA sequence variations in individuals and can serve as important genetic markers. Recently, investigations of gene-based and whole genome-based SNPs have been applied to association studies for marker discovery. However, SNPs are so population-specific that the association needs to be verified. Fifty-five genes and 384 SNPs were selected based on association with disease. Genotypes of 337 SNPs in candidate genes were determined using Illumina Sentrix Array Matrix (SAM) chips by an allele-specific extension method in 364 unrelated Korean individuals. Allelic frequencies of SNPs were compared with those of other populations obtained from the International HapMap database. Minor allele frequencies, linkage disequilibrium blocks, tagSNPs, and haplotypes of functional candidate SNPs in 55 genetic disease-associated genes were provided. Our data may provide useful information for the selection of genetic markers for gene-based genetic disease-association studies of the Korean population.