Submitted to: Yeasts International Symposium
Publication Type: Abstract Only
Publication Acceptance Date: July 6, 2007
Publication Date: July 1, 2007
Citation: Liu, Z., Palmquist, D.E. 2007. A robust standard for absolute mRNA quantification of Saccharomyces cerevisiae by qRT-PCR using the universal RNA controls [abstract]. Yeasts International Symposium. Abstract No. S-84. Technical Abstract: Recently developed universal external RNA controls allow comparison of expression data generated from microarray and real time qRT-PCR, including SYBR Green and TaqMan-probe based chemistry. It provides reliable controls for data normalization and analysis. In this study, we further developed strategies of the control applications for qRT-PCR, allowing simple and robust absolute quantification of mRNA under varied conditions. Six replicated reactions were performed for each control and furfural-HMF stress condition (30 mM each) for the ethanologenic yeast Saccharomyces cerevisiae. Eight proven differentially expressed genes under the defined conditions were evaluated. Control gene Ctrl_Gm5 was designated as a normalization reference at a fixed threshold during data acquisition and analysis for each reaction run. Using a general linear model and a weighted means regression analyses, we generated a master equation of linear regression (R(2)=0.9996) for cycle numbers as a function of log (mRNA) over conditions for all reactions. Equations derived from each condition and each reaction run did not show significant differences from the master equation at p less than or equal to 0.05. Confidence intervals for the regression coefficients at the 95% level were constant in showing equality of slopes and intercepts under different conditions. We conclude that any equation generated by the RNA control is consistent and can be used as a robust normalization standard for mRNA estimate at any conditions. Using our method with the universal RNA controls, we simplified absolute quantification procedures, enhanced assay function and efficiency of qRT-PCR, and made it a true high-throughput platform for reliable quantitative expression analysis.