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Title: The use of real-time reverse transcriptase PCR for the quantification of cytokine gene expression
Authors: Overbergh, Lutgart
Giulietti, Annapaula
Valckx, Dirk
Decallonne, Brigitte
Bouillon, Roger
Mathieu, Chantal # ×
Issue Date: Mar-2003
Series Title: Journal of Biomolecular Techniques vol:14 issue:1 pages:33-43
Abstract: Real-time reverse transcriptase polymerase chain reaction (RT-PCR) is becoming a widely used method to quantify cytokines from cells, tissues, or tissue biopsies. The method allows for the direct detection of PCR product during the exponential phase of the reaction, combining amplification and detection in a single step. Using TaqMan chemistry (Applied Biosystems, Foster City, CA) and the ABI Prism 7700 Sequence Detection System (Applied Biosystems), we validated a large panel of murine and human cytokines, as we as other factors playing a role in the immune system, such a chemokines and apoptotic markers. Although the method allows fast, sensitive, and accurate quantification, different control assays are necessary for the method to be reliable. By construction of complementary DNA (cDNA) plasmid clones, standard curves are generated that allow direct quantification of every unknown sample. Furthermore, the choice of a reliable housekeeping gene is very important. Finally, co-amplification of contaminating genomic DNA is avoided by designing sets of primers located in different exons or or intron-exon junctions. In conclusion, the real-time RT-PCF technique is very accurate and sensitive, allows high through put, and can be performed on very small samples.The development of real-time RT-PCR has resulted in an exponential increase in its use over the last couple of years, and the method has undoubtedly become the standard for quantifying cytokine patterns, clarifying many functional properties of immune cells and their associated diseases.
URI: 
ISSN: 1524-0215
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Clinical and Experimental Endocrinology
Research Group Experimental Neurology
× corresponding author
# (joint) last author

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