• Journal of Veterinary Science
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• 제24권3호
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• pp.40.1-40.6
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• 2023

Analysis of the VP1 gene sequence of the foot and mouth disease virus (FMDV) is critical to understanding viral evolution and disease epidemiology. A standard set of primers have been used for the detection and sequence analysis of the VP1 gene of FMDV directly from suspected clinical samples with limited success. The study validated VP1-specific degenerate primer-based reverse transcription polymerase chain reaction (RT-PCR) for the qualitative detection and sequencing of serotype O FMDV lineages circulating in India. The novel degenerate primer-based RT-PCR amplifying the VP1 gene can circumvent the genetic heterogeneity observed in viruses after cell culture adaptation and facilitate precise viral gene sequence analysis from clinical samples.

• Biomolecules & Therapeutics
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• 제26권3호
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• pp.290-297
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• 2018

We aimed to understand the molecular changes in host cells that accompany infection by the seasonal influenza A H1N1 virus because the initial response rapidly changes owing to the fact that the virus has a robust initial propagation phase. Human epithelial alveolar A549 cells were infected and total RNA was extracted at 30 min, 1 h, 2 h, 4 h, 8 h, 24 h, and 48 h post infection (h.p.i.). The differentially expressed host genes were clustered into two distinct sets of genes as the infection progressed over time. The patterns of expression were significantly different at the early stages of infection. One of the responses showed roles similar to those associated with the enrichment gene sets to known 'gp120 pathway in HIV.' This gene set contains genes known to play roles in preventing the progress of apoptosis, which infected cells undergo as a response to viral infection. The other gene set showed enrichment of 'Drug Metabolism Enzymes (DMEs).' The identification of two distinct gene sets indicates that the virus regulates the cell's mechanisms to create a favorable environment for its stable replication and protection of gene metabolites within 8 h.

• Genomics & Informatics
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• 제2권2호
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• pp.92-98
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• 2004

A cDNA microarray experiment is one of the most useful high-throughput experiments in medical informatics for monitoring gene expression levels. Statistical analysis with a cDNA microarray medical data requires a normalization procedure to reduce the systematic errors that are impossible to control by the experimental conditions. Despite the variety of normalization methods, this. paper suggests a more general and synthetic normalization algorithm with a control gene set based on previous studies of normalization. Iterative normalization method was used to select and include a new control gene set among the whole genes iteratively at every step of the normalization calculation initiated with the housekeeping genes. The objective of this iterative normalization was to maintain the pattern of the original data and to keep the gene expression levels stable. Spatial plots, M&A (ratio and average values of the intensity) plots and box plots showed a convergence to zero of the mean across all genes graphically after applying our iterative normalization. The practicability of the algorithm was demonstrated by applying our method to the data for the human photo aging study.

• Toxicological Research
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• 제32권4호
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• Journal of Information Processing Systems
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• 제3권1호
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• pp.38-42
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• 2007

Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of functional information from a large corpus of gene expression data is still a time-consuming task. In this paper, we propose an efficient method for identifying functional categories of differentially expressed genes from a micro-array experiment by using Gene Ontology (GO). Our method is as follows: (1) The expression data set is first filtered to include only genes with mean expression values that differ by at least 3-fold between the two groups. (2) The genes are then ranked based on the t-statistics. The 100 most highly ranked genes are selected as informative genes. (3) The t-value of each informative gene is imposed as a score on the associated GO terms. High-scoring GO terms are then listed with their associated genes and represent the functional category information of the micro-array experiment. A system called HMDA (Hallym Micro-array Data analysis) is implemented on publicly available micro-array data sets and validated. Our results were also compared with the original analysis.

• Genomics & Informatics
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• 제16권4호
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• pp.36.1-36.3
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• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• Genomics & Informatics
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• 제9권4호
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• pp.173-180
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• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.

• Journal of Ginseng Research
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• 제44권3호
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• pp.519-526
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• 2020

Background: Bisphenol A (BPA), known as an endocrine disruptor, is widely used in the world. BPA is reported to cause inflammation-related diseases. Korean Red Ginseng (KRG) has been used safely in human for a long time for the treatment of diverse diseases. KRG has been reported of its mitigating effect on menopausal symptoms and suppress adipose inflammation. Here, we investigate the protective effect of orally administered KRG on the impacts of BPA in the liver and uterus of menopausal mice model. Methods: The transcriptome analysis for the effects of BPA on mice liver was evaluated by Gene Expression Omnibus (GEO) database-based data (GSE26728). In vivo assay to evaluate the protective effect of KRG on BPA impact in ovariectomized (OVX) mice were designed and analyzed by RNA sequencing. Results: We first demonstrated that BPA induced 12 kinds of gene set in the liver of normal mice. The administration of BPA and KRG did not change body, liver, and uterine weight in OVX mice. KRG downregulated BPA-induced inflammatory response and chemotaxis-related gene expression. Several gene set enrichment analysis (GSEA)-derived inflammatory response genes increased by BPA were inhibited by KRG in OVX mice. Conclusion: Our data suggest that BPA has commonly influenced inflammatory response effects on both normal and OVX mice. KRG protects against BPA impact of inflammatory response and chemotaxis in OVX mouse models. Our comparative analysis will provide new insight into the efficacy of KRG on endocrine disrupting chemicals and OVX mouse.

• Genomics & Informatics
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• 제4권3호
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• pp.110-117
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• 2006

In microarray technology, many diverse experimental features can cause biases including RNA sources, microarray production or different platforms, diverse sample processing and various experiment protocols. These systematic effects cause a substantial obstacle in the analysis of microarray data. When such data sets derived from different experimental processes were used, the analysis result was almost inconsistent and it is not reliable. Therefore, one of the most pressing challenges in the microarray field is how to combine data that comes from two different groups. As the novel trial to integrate two data sets with batch effect, we simply applied standardization to microarray data before the significant gene selection. In the gene selection step, we used new defined measure that considers the distance between a gene and an ideal gene as well as the between-slide and within-slide variations. Also we discussed the association of biological functions and different expression patterns in selected discriminative gene set. As a result, we could confirm that batch effect was minimized by standardization and the selected genes from the standardized data included various expression pattems and the significant biological functions.

• BMB Reports
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• 제29권3호
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• pp.272-275
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• 1996

The expression of genes induced by Dichloroacetate (DCA) treatment was analyzed by mRNA differential display. Purified total RNAs from rat liver treated with saline or DCA (100 mg/100 g b.w.) were reverse transcribed by using a set of oligonucleotide primers. The PCR products were resolved on a denaturing sequencing gel. PCR band representing mRNA expressed specifically in DCA-treated liver was excised and reamplified by PCR. A 120-bp c-DNA clone named IC1 was isolated and the DNA sequence of IC1 was analyzed. IC1 revealed 50% homology with 3' end of a mouse fibroblast growth factor mRNA This result indicates that DCA induces the expression of a gene which has a 50% homology with a Mouse fibroblast growth factor, and expression of this gene might be involved in non genotoxic process caused by DCA.