• Molecular & Cellular Toxicology
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• v.1 no.2
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• pp.92-98
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• 2005

DNA microarray analysis of gene expression in toxicogenomics typically requires relatively large amounts of total RNA. This limits the use of DNA microarray when the sample available is small. To confront this limitation, different methods of linear RNA amplification that generate antisense RNA (aRNA) have been optimized for microarray use. The target preparation strategy using amplified RNA in DNA microarray protocol can be divided into direct-incorporation labeling which resulted in cDNA targets (Cy-dye labeled cDNA from aRNA) and indirect-labeling which resulted in cRNA targets (i.e. Cy-dye labeled aRNA), respectively. However, despite the common use of amplified targets (cDNA or cRNA) from aRNAs, no systemic assessment for the use of amplified targets and bias in terms of hybridization performance has been reported. In this investigation, we have compared the hybridization performance of cRNA targets with cDNA targets from aRNA on a 10 K cDNA microarrays. Under optimized hybridization conditions, we found that 43% of outliers from cDNA technique and 86% from the outlier genes were reproducibly detected by both targets hybridization onto cDNA microarray. This suggests that the cRNA labeling method may have a reduced capacity for detecting the differential gene expression when compared to the cDNA target preparation. However, further validation of this discordant result should be pursued to determine which techniques possesses better accuracy in identifying truly differential genes.

• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.347-356
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• 2008

High-throughput microarray is one of the most popular tools in molecular biology, and various computational methods have been developed for the microarray data analysis. While the computational methods easily extract significant features, it suffers from inferring modules of multiple co-regulated genes. Hypernetworhs are motivated by biological networks, which handle all elements based on their combinatorial processes. Hence, the hypernetworks can naturally analyze the biological effects of gene combinations. In this paper, we introduce a hypernetwork classifier for microRNA (miRNA) profile analysis based on microarray data. The hypernetwork classifier uses miRNA pairs as elements, and an evolutionary learning is performed to model the microarray profiles. miTNA modules are easily extracted from the hypernetworks, and users can directly evaluate if the miRNA modules are significant. For experimental results, the hypernetwork classifier showed 91.46% accuracy for miRNA expression profiles on multiple human canters, which outperformed other machine learning methods. The hypernetwork-based analysis showed that our approach could find biologically significant miRNA modules.

• Reproductive and Developmental Biology
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• v.32 no.4
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• pp.229-235
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• 2008

Silencing of Dicer1 by siRNA did not inhibit development up to the blastocyst stage, but decreased expression of selected transcription factors, including Oct-4, Sox2 and Nanog, suggesting that Dicer1 gene expression is associated with differentiation processes at the blastocyst stage (Cui et al., 2007). In order to get insights into genes which may be linked with microRNA system, we compared gene expression profiles in Gapdh and Dicer1 siRNA-microinjected blastocysts using the Applied Biosystem microarray technology. Our data showed that 397 and 737 out of 16354 genes were up- and down-regulated, respectively, following siRNA microinjection (p<0.05), including 24 up- and 28 down-regulated transcription factors. Identification of genes that are preferentially expressed at particular Dicer1 knock down embryos provides insights into the complex gene regulatory networks that drive differentiation processes in embryos at blastocyst stage.

• Journal of Environmental Science International
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• v.24 no.5
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• pp.623-631
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• 2015

Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). This study, the mRNA expression profiles provide insight into the mechanism of action of cadmium in Fleshy shrimp (Fenneropenaeus chinensis). The ability of genomic technologies was contributed decisively to development of new molecular biomarkers and to the determination of new possible gene targets. Also, it can be approach for monitoring of trace metal using oligo-chip microarray-based in potential model marine user level organisms. 15K oligo-chip for F. chinensis that include mostly unique sets of genes from cDNA sequences was developed. A total of 13,971 spots (1,181 mRNAs up- regulated and 996 down regulated) were identified to be significantly expressed on microarray by hierarchical clustering of genes after exposure to cadmium for different conditions (Cd24-5000 and Cd48-1000). Most of the changes of mRNA expression were observed at the long time and low concentration exposure of Cd48-1000. But, gene ontology analysis (GO annotation) were no significant different between experiments groups. It was observed that mRNA expression of main genes involved in metabolism, cell component, molecular binding and catalytic function. It was suggested that cadmium inhibited metabolism and growth of F. chinensis.

• Molecules and Cells
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• v.40 no.10
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• pp.714-730
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• 2017

Pre-mRNA splicing further increases protein diversity acquired through evolution. The underlying driving forces for this phenomenon are unknown, especially in terms of gene expression. A rice alternatively spliced transcript detection microarray (ASDM) and RNA sequencing (RNA-Seq) were applied to differentiate the transcriptome of 4 representative organs of Oryza sativa L. cv. Ilmi: leaves, roots, 1-cm-stage panicles and young seeds at 21 days after pollination. Comparison of data obtained by microarray and RNA-Seq showed a bell-shaped distribution and a co-lineation for highly expressed genes. Transcripts were classified according to the degree of organ enrichment using a coefficient value (CV, the ratio of the standard deviation to the mean values): highly variable (CVI), variable (CVII), and constitutive (CVIII) groups. A higher index of the portion of loci with alternatively spliced transcripts in a group (IAST) value was observed for the constitutive group. Genes of the highly variable group showed the characteristics of the examined organs, and alternatively spliced transcripts tended to exhibit the same organ specificity or less organ preferences, with avoidance of 'organ distinctness'. In addition, within a locus, a tendency of higher expression was found for transcripts with a longer coding sequence (CDS), and a spliced intron was the most commonly found type of alternative splicing for an extended CDS. Thus, pre-mRNA splicing might have evolved to retain maximum functionality in terms of organ preference and multiplicity.

• Bulletin of the Korean Chemical Society
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• v.29 no.6
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• pp.1137-1140
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• 2008

M1 RNA, the catalytic subunit of Escherichia coli RNase P, is an essential ribozyme that processes the 5' leader sequence of tRNA precursors (ptRNAs). Using KS2003, an E. coli strain generating only low levels of M1 RNA, which showed growth defects, we examined whether M1 RNA is involved in polycistronic mRNA processing or degradation. Microarray analysis of total RNA from KS2003 revealed six polycistronic operon mRNAs (acpP-fabF, cysDNC, flgAMN, lepAB, phoPQ, and puuCBE) showing large differences in expression between the adjacent genes in the same mRNA transcript compared with the KS2001 wild type strain. Model substrates spanning an adjacent pair of genes for each polycistronic mRNA were tested for RNase P cleavage in vitro. Five model RNAs (cysNC, flgMN, lepAB, phoPQ, and puuBE) were cleaved by RNase P holoenzyme but not by M1 RNA alone. However, the cleavages occurred at non-ptRNA-like cleavage sites, with much less efficiency than the cleavage of ptRNA. Since cleavage products generated by RNase P from a polycistronic mRNA can have different in vivo stabilities, our results suggest that RNase P cleavage may lead to differential expression of each cistron.

• Journal of Animal Science and Technology
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• v.52 no.4
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• pp.329-336
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• 2010

Myogenic satellite cells (MSCs) are mononuclear, multipotent progenitors of adult skeletal muscle possessing a capacity of forming adipocyte-like cells (ALC). To identify the skeletal muscle type-specific myogenic and adipogenic genes during MSCs differentiation, total RNA was extracted from bovine MSCs, myotube-formed cell (MFC), and ALC from each of Beef shank, Longissimus dorsi, Deep pectoral, and Semitendinosus. DNA microarray analysis (24,000 oligo chip) comparing MSCs with MFC and ALC, respectively, revealed 135 differentially expressed genes (> 4 fold) among four cuts. Real-time PCR confirmed expression of 29 genes. Furthermore, the whole tissue sample RNAs analysis showed 6 differentially expressed genes in Beef shank. Among which, 1 gene in MSCs, 4 in MFC, and 1 in ALCs were highly expressed. This study will provide an insight for better understanding the molecular mechanism of differentiation of skeletal muscle type-specific MSCs. The identified genes may be used as marker to distinguish skeletal muscle types.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2005.10a
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• pp.109-109
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• 2005

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2005.10a
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• pp.109-109
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• 2005

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.366-370
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• 2005

Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.