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Simultaneous gene expression analysis of steady-state and actively translated mRNA populations from osteosarcoma MG-63 cells in response to IL-1 via an open expression analysis platform
Author(s) -
Jingfang Ju
Publication year - 2003
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkg702
Subject(s) - biology , gene expression , gene , polysome , messenger rna , regulation of gene expression , microbiology and biotechnology , complementary dna , population , genetics , rna , ribosome , demography , sociology
Pro-inflammatory cytokines play a key role in various forms of metabolic bone diseases, including osteopenia and osteoporosis. Human MG-63 cells treated with IL-1alpha were used as a model system to identify potential marker genes that are differentially expressed. This study is designed to quantitate gene expression of actively translated mRNAs as compared to the steady-state mRNA population. Both steady-state mRNAs and actively translated mRNAs from control MG-63 cells and MG-63 cells treated with IL-1alpha were isolated and converted to cDNA. The gene expression analysis from these samples was then quantitated with an open expression analysis platform with no requirement for a priori knowledge of sequence information. As a result, many differentially regulated genes were discovered via IL-1alpha treatment. Some of the genes have been described previously as playing important roles in the regulation of inflammation and cell adhesion. These comparisons provided a panoramic overview of gene expression at both the total transcript and post-transcriptional levels. In addition, the quantitation of actively translated mRNAs associated with polysomes also provided a better estimation of protein expression levels. This methodology allows for the identification of genes acutely regulated during translation. Furthermore, the process may aid in the identification of new drug targets or biomarkers.

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